Abstract
We consider a Bertrand duopoly model with unknown costs. The firms' aim is to choose the price of its product according to the well-known concept of Bayesian Nash equilibrium. The chooses are made simultaneously by both firms. In this paper, we suppose that each firm has two different technologies, and uses one of them according to a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We show that this game has exactly one Bayesian Nash equilibrium. We analyse the advantages, for firms and for consumers, of using the technology with highest production cost versus the one with cheapest production cost. We prove that the expected profit of each firm increases with the variance of its production costs. We also show that the expected price of each good increases with both expected production costs, being the effect of the expected production costs of the rival dominated by the effect of the own expected production costs.

Abstract
This work addresses a humidity sensor using long-period fiber gratings (LPG) coated with silica nanospheres film. SiO2-nanospheres coating is deposited onto the LPG using the electrostatic self-assembly technique (ESA). The polymeric overlay changes its optical properties when exposed to different humidity levels, resulting in a shift of the resonance wavelength of the LPG. The obtained results are accordant with the theoretical simulations. Wavelength shifts up to 12nm in a humidity range from 20% to 80% are reported, maintaining the same dependence at different temperatures.

Abstract

Abstract
In gametophytic self-incompatibility systems, many specificities (different 'lock-and-key' combinations) are maintained by frequency-dependent selection for very long evolutionary times. In Solanaceae, trans-specific evolution (the observation that an allele from one species may be more closely related to an allele from another species than to others from the same species) has been taken as an argument for the very old age of specificities. In this work, by determining, for the first time, the age of extant Prunus species, we show that this reasoning cannot be applied to Prunoideae. Furthermore, since our sample size is large (all S-RNase encoding the female component and SFB encoding the male component GenBank sequences), we were able to estimate the age of the oldest Prunus specificities. By doing so, we show that the lower variability levels at the Prunus S-locus, in comparison with Solanaceae, is due to the younger age of Prunus alleles, and not to a difference in silent mutation rates. We show that the ancestor to extant Prunus species harboured at least 102 specificities, in contrast to the maximum of 33 observed in extant Prunus species. Since the number of specificities that can be maintained in a population depends on the effective population size, this observation suggests a bottleneck in Prunus evolutionary history. Loss of specificities may have occurred during this event. Using only information on amino acid sites that determine specificity differences, and a simulation approach, we show that a model that assumes closely related specificities are not preferentially lost during evolution, fails to predict the observed degree of specificity relatedness.

Abstract
Breast cancer conservative treatment (BCCT) is considered the gold standard of breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardised way. The limited reproducibility of subjective aesthetic evaluation in BCCT forced the research on objective methods. A recent computer system was developed to objectively and automatically evaluate the aesthetic result of BCCT In this system, the detection of the breast contour on the digital photograph of the patient is necessary to extract the features subsequently used in the evaluation process. In this paper we extend an algorithm based on the shortest path on a graph to detect automatically the breast contour. The advantage of graph algorithms is that they are guaranteed to find the global optimum of the problem; the difficulty is that they make it hard to enforce shape constraints. We define and compare different techniques to introduce the a priory knowledge of the mammary contour. Experimental results show that the proposed techniques consistently outperform the base method.

Abstract
Due to its combinatorial nature, the Unit Commitment problem has for long been an important research challenge, with several optimization techniques, from exact to heuristic methods, having been proposed to deal with it. In line with one current trend of research, metaheuristic approaches have been studied and some interesting results have already been achieved and published. However, a successful utilization of these methodologies in practice, when embedded in Energy Management Systems, is still constrained by the reluctance of industrial partners in using techniques whose performance highly depends on a correct parameter tuning. Therefore, the application of metaheuristics to the Unit Commitment problem does still justify further research. In this paper we propose a new search strategy, for Local Search based metaheuristics, that tries to overcome this issue. The approach has been tested in a set of instances, leading to very good results in terms of solution cost, when compared either to the classical Lagrangian Relaxation or to other metaheuristics. It also drastically reduced the computation times. Furthermore, the approach proved to be robust, always leading to good results independently of the metaheuristic parameters used.