Abstract
By means of a cross-cultural virtual teams project involving classrooms in Scotland, Germany, and Portugal, students were exposed to the challenges of collaborating internationally with the intention of increasing their intercultural competency. Intercultural sensitivity and intercultural communication competency were measured using responses to surveys before and after the 6-week project. Students reported, among other aspects, a heightened awareness of the difficulties of intercultural communication. Despite a general appreciation of the project and its outcomes, negative results, such as an increased dislike of intercultural interaction, emerged. Contradictory results warrant further investigation with data from future collaborations.

Abstract
In this paper we investigate three different types of infinitive constructions involving para in European Portuguese, viz. purpose clauses, complement clauses in which para behaves as a true complementizer and complement clauses in which para behaves as a preposition pertaining to the main sentence. We begin with a brief characterization of the Portuguese simple infinitive, arguing that, in appropriate conditions, it exhibits defective temporal properties that are, nonetheless, non-specified whenever another component in the sentence ascribes temporal information to the infinitive clause. Then we compare the three constructions under analysis: although there are clear divergences in their semantic behaviour, we observe that in all cases the situation represented by the infinitive clause is systematically located in an interval that follows its Temporal Perspective Point provided by the main clause. In order to account for this regularity, we propose that, in these contexts, (i) the infinitive is non-specified regarding its temporal features and (ii) the lexical properties of para are responsible for the posteriority reading stated above.

Abstract
This paper proposes the linear frequency cepstral coefficients as highly discriminative features for anomaly detection in ball bearings using vibration sensor data. These features are based on cepstral analysis and are capable of encoding the patterns of a spectral magnitude profile. Incipient damages on bearings can grow rapidly under normal use resulting in vibration and harsh noise. If left undetected, this damage will worsen, leading to high maintenance costs or even injury. Multiple interferences in an industrial environment contaminate the signal, making it a challenge to correctly identify the bearings' condition. Many studies have attempted to overcome this issue at the signal level. However, the discriminative capacity of the current vibration signal features is still vulnerable to interference, which motivates this work. In order to demonstrate the benefits of these features, we (1) show that they are computationally efficient and suitable for real-time incremental training; (2) conduct discriminative analysis by evaluating the separability performance and comparing it with the state of the art; and (3) test the robustness of the proposed features under noise interference, which is ideal for use in the harsh operating conditions of industrial machinery. The data was obtained from a laboratory workbench setting that reproduces bearing fault scenarios. Results show that the proposed features are fast, competitive when compared to state-of-the-art features, and resilient to high levels of interference. Despite the higher performance when using the quadratic model, the proposed features remain highly discriminative when used with several other discriminant function.

Abstract
Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP) is a neurological genetic disease that propagates from one family generation to the next. The disease can have severe effects on the life of patients after the first symptoms (onset) appear. Accurate prediction of the age of onset for these patients can help the management of the impact. This is, however, a challenging problem since both familial and non-familial characteristics may or may not affect the age of onset. In this work, we assess the importance of sets of genealogical features used for Predicting the Age of Onset of TTR-FAP Patients. We study three sets of features engineered from clinical and genealogical data records obtained from Portuguese patients. These feature sets, referred to as Patient, First Level and Extended Level Features, represent sets of characteristics related to each patient's attributes and their familial relations. They were compiled by a Medical Research Center working with TTR-FAP patients. Our results show the importance of genealogical data when clinical records have no information related with the ancestor of the patient, namely its Gender and Age of Onset. This is suggested by the improvement of the estimated predictive error results after combining First and Extended Level with the Patients Features.

Abstract
Building upon the success of the first edition, we organize the second edition of the Text2Story Workshop on Narrative Extraction from Texts in conjunction with the 41^st European Conference on Information Retrieval (ECIR 2019) on April 14, 2019. Our objective is to further consolidate the efforts of the community and reflect upon the progress made since the last edition. Although the understanding of natural language has improved over the last couple of years – with research works emerging on the grounds of information extraction and text mining – the problem of constructing consistent narrative structures is yet to be solved. It is expected that the state-of-the-art has been advancing in pursuit of methods that automatically identify, interpret and relate the different elements of narratives which are often spread among different sources. In the second edition of the workshop, we foster the discussion of recent advances in the link between Information Retrieval (IR) and formal narrative representations from text.

Abstract