Seasonal patterns of polycyclic aromatic hydrocarbons in digestive gland and arm of octopus (Octopus vulgaris) from the Northwest Atlantic

Among organic pollutants existing in coastal areas, polycyclic aromatic hydrocarbons (PAHs) are of great concern due to their ubiquity and carcinogenic potential. The aim of this study was to evaluate the seasonal patterns of PAHs in the digestive gland and arm of the common octopus (Octopus vulgaris) from the Northwest Atlantic Portuguese coast. In the different seasons, 18 PAHs were determined and the detoxification capacity of the species was evaluated. Ethoxyresorufin O-deethylase (EROD) and ethoxycoumarin O-deethylase (ECOD) activities were measured to assess phase I biotransformation capacity. Individual PAH ratios were used for major source (pyrolytic/petrogenic) analysis. Risks for human consumption were determined by the total toxicity equivalence approach. Generally, low levels of PAHs were detected in the digestive gland and in the arm of octopus, with a predominance of low molecular over high molecular weight compounds. PAHs exhibited seasonality in the concentrations detected and in their main emission sources. In the digestive gland, the highest total PAH levels were observed in autumn possibly related to fat availability in the ecosystem and food intake. The lack of PAH elimination observed in the digestive gland after captivity could be possibly associated to a low biotransformation capacity, consistent with the negligible/undetected levels of EROD and ECOD activity in the different seasons. The emission sources of PAHs found in the digestive gland varied from a petrogenic profile observed in winter to a pyrolytic pattern in spring. In the arm, the highest PAH contents were observed in June; nevertheless, levels were always below the regulatory limits established for food consumption. The carcinogenic potential calculated for all the sampling periods in the arm were markedly lower than the ones found in various aquatic species from different marine environments. The results presented in this study give relevant baseline data for environmental monitoring of organic pollution in coastal areas.

Sequencing cutting patterns with colored interval graphs

The problem addressed here originates in the industry of flat glass cutting and wood panel sawing, where smaller items are cut from larger items accordingly to predefined cutting patterns. In this type of industry the smaller pieces that are cut from the patterns are piled around the machine in stacks according to the size of the pieces, which are moved to the warehouse only when all items of the same size have been cut. If the cutting machine can process only one pattern at a time, and the workspace is limited, it is desirable to set the sequence in which the cutting patterns are processed in a way to minimize the maximum number of open stacks around the machine. This problem is known in literature as the minimization of open stacks (MOSP). To find the best sequence of the cutting patterns, we propose an integer programming model, based on interval graphs, that searches for an appropriate edge completion of the given graph of the problem, while defining a suitable coloring of its vertices.

Bipedal Locomotion: A Fractional CPG for Generating Patterns

Proceedings of the 10th Conference on Dynamical Systems Theory and Applications

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.