Segmentation and Clustering of Textual Sequences: a Typological Approach

The long term goal of this research is to develop a program able to produce an automatic segmentation and categorization of textual sequences into discourse types. In this preliminary contribution, we present the construction of an algorithm which takes a segmented text as input and attempts to produce a categorization of sequences, such as narrative, argumentative, descriptive and so on. Also, this work aims at investigating a possible convergence between the typological approach developed in particular in the field of text and discourse analysis in French by Adam (2008) and Bronckart (1997) and unsupervised statistical learning.

Exploring the relative DNA contribution of first and second object's users on mock touch DNA mixtures

Contact stains recovered at break-in crime scenes are frequently characterized by mixtures of DNA from several persons. Broad knowledge on the relative contribution of DNA left behind by different users overtime is of paramount importance. Such information might help crime investigators to robustly evaluate the possibility of detecting a specific (or known) individual's DNA profile based on the type and history of an object. To address this issue, a contact stain simulation-based protocol was designed. Fourteen volunteers either acting as first or second object's users were recruited. The first user was required to regularly handle/wear 9 different items during an 8-10-day period, whilst the second user for 5, 30 and 120 min, in three independent simulation sessions producing a total of 231 stains. Subsequently, the relative DNA profile contribution of each individual pair was investigated. Preliminary results showed a progressive increase of the percentage contribution of the second user compared to the first. Interestingly, the second user generally became the major DNA contributor when most objects were handled/worn for 120 min, Furthermore, the observation of unexpected additional alleles will then prompt the investigation of indirect DNA transfer events.

Most and Least Preferred Colours Differ According to Object Context : New Insights from an Unrestricted Colour Range

Humans like some colours and dislike others, but which particular colours and why remains to be understood. Empirical studies on colour preferences generally targeted most preferred colours, but rarely least preferred (disliked) colours. In addition, findings are often based on general colour preferences leaving open the question whether results generalise to specific objects. Here, 88 participants selected the colours they preferred most and least for three context conditions (general, interior walls, t-shirt) using a high-precision colour picker. Participants also indicated whether they associated their colour choice to a valenced object or concept. The chosen colours varied widely between individuals and contexts and so did the reasons for their choices. Consistent patterns also emerged, as most preferred colours in general were more chromatic, while for walls they were lighter and for t-shirts they were darker and less chromatic compared to least preferred colours. This meant that general colour preferences could not explain object specific colour preferences. Measures of the selection process further revealed that, compared to most preferred colours, least preferred colours were chosen more quickly and were less often linked to valenced objects or concepts. The high intra- and inter-individual variability in this and previous reports furthers our understanding that colour preferences are determined by subjective experiences and that most and least preferred colours are not processed equally.