Dynamics of pneumococcal nasopharyngeal carriage in healthy children attending a day care center in northern Spain. Influence of detection techniques on the results

8 p.

A note on collusion sustainability with optimal punishments and detection lags

In this note we characterize optimal punishments with detection lags when the market consists of n oligopolistic firms. We extend a previous note by Colombo and Labrecciosa (2006) [Colombo, L., and Labrecciosa, P., 2006. Optimal punishments with detection lags. Economic Letters 92, 198-201] to show how in the presence of detection lags optimal punish- ments fail to restore cooperation also in markets with a low number of firms.

Flood risk management: What are the main drivers of prevention?

4 p.

On the optimal usage of labelled examples in semi-supervised multi-class classification problems

In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.

Seroprevalence of Triatoma virus (Dicistroviridae: Cripaviridae) antibodies in Chagas disease patients

Background: Chagas disease is caused by Trypanosoma cruzi, and humans acquire the parasite by exposure to contaminated feces from hematophagous insect vectors known as triatomines. Triatoma virus (TrV) is the sole viral pathogen of triatomines, and is transmitted among insects through the fecal-oral route and, as it happens with T. cruzi, the infected insects release the virus when defecating during or after blood uptake. Methods: In this work, we analysed the occurrence of anti-TrV antibodies in human sera from Chagas disease endemic and non-endemic countries, and developed a mathematical model to estimate the transmission probability of TrV from insects to man, which ranged between 0.00053 and 0.0015. Results: Our results confirm that people with Chagas disease living in Bolivia, Argentina and Mexico have been exposed to TrV, and that TrV is unable to replicate in human hosts. Conclusions: We presented the first experimental evidence of antibodies against TrV structural proteins in human sera.