Abstract
Previous studies demonstrated the capability of mixed culture DC1 to mineralize the thiocarbamate herbicide molinate through the activity of molinate hydrolase (MolA). Because liquid suspensions are not compatible with long-term storage and are not easy to handle when bioremediation strategies are envisaged, in this study spray drying was evaluated as a cost-effective method to store and transport these molinate biocatalysts. Microparticles of mixed culture DC1 (DC1) and of cell free crude extracts containing MolA (MA) were obtained without any carrier polymer, and with calcium alginate (CA) or modified chitosan (MCt) as immobilizing agents. All the DC1 microparticles showed high molinate degrading activity upon storage for 6 months, or after 9 additions of similar to 0.4 mM molinate over 1 month. The DC1-MCt microparticles were those with the highest survival rate and lowest heterogeneity. For MA microparticles, only MA-MCt degraded molinate. However, its V-max was only 1.4% of that of the fresh cell free extract (non spray dried). The feasibility of using the DC1-MCt and MA-MCt microparticles in bioaugmentation processes was assessed in river water microcosms, using mass (g):volume (L) ratios of 1:13 and 1:0.25, respectively. Both type of microparticles removed 65-75% of the initial 1.5 mg L-1 molinate, after 7 days of incubation. However, only DC1-MCt microparticles were able to degrade this environmental concentration of molinate without disturbing the native bacterial community. These results suggest that spray drying can be successfully used to produce DC1-MCt microparticles to remediate molinate polluted sites through a bioaugmentation strategy.

Abstract
This paper describes a robot with 12 degrees of freedom for pick-and-place operations using bricks. In addition, an optimization approach is proposed, which determines the state of each joint (that establishes the pose for the robot) based on the target position while minimizing the effort of the servomotors avoiding the inverse kinematics problem, which is a hard task for a 12 DOF robot manipulator. Therefore, it is a multi-objective optimization problem that will be solved using two optimization methods: the Stretched Simulated Annealing method and the NSGA II method. The experiments conducted in a simulation environment prove that the proposed approach is able to determine a solution for the inverse kinematics problem. A real robot formed by several servomotors and a gripper is also presented in this research for validating the solutions.

Abstract
Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures.

Abstract
Previously, two municipal solid waste commercial composts (MSW1 and MSW2) were characterized. Although sharing the same type of raw material, most of their physicochemical, stability and maturity properties differed. The present study aimed to characterize them at a microbiological level, and to infer on possible relationships between the composts properties and the structure of their bacterial communities. Both the 16S rRNA gene-based PCR-DGGE profiling and 454-pyrosequencing technology showed that the structure of the bacterial communities of these composts was distinct. The bacterial community of MSW1 was more diverse than that of MSW2. Multivariate analyses revealed that the high electrical conductivity, Cu content as well as the low phytotoxity of compost MSW1, when compared to MSW2, contributed most to shape its bacterial community structure. Indeed, high abundance of halophilic (Halomonadaceae and Brevibacteriaceae) and metal resistant organisms (Brevibacteriaceae and Bacillaceae) were found in MSW1. In addition, Pseudonocardiaceae, Streptomycetaceae, Bacillaceae, and Brevibacteriaceae may have contributed to the high humic-like acids content and low phytotoxicity of MSW1. In contrast, the high organic matter content and the high density of the cultivable fungi population were the parameters most correlated with the structure of the bacterial community of compost MSW2, dominated by Corynebacteriaceae and mainly Aerococcaceae, taxonomic groups not commonly found in composts.

Abstract
Machine learning approaches often focus on optimizing the algorithm rather than assuring that the source data is as rich as possible. However, when it is possible to enhance the input examples to construct models, one should consider it thoroughly. In this work, we propose a technique to define the best set of training examples using dynamic ensembles in text classification scenarios. In dynamic environments, where new data is constantly appearing, old data is usually disregarded, but sometimes some of those disregarded examples may carry substantial information. We propose a method that determines the most relevant examples by analysing their behaviour when defining separating planes or thresholds between classes. Those examples, deemed better than others, are kept for a longer time-window than the rest. Results on a Twitter scenario show that keeping those examples enhances the final classification performance.

Abstract
For Anosov flows obtained by suspensions of Anosov diffeomorphisms on surfaces, we show the following type of rigidity result: if a topological conjugacy between them is differentiable at a point, then the conjugacy has a smooth extension to the suspended 3-manifold. This result generalizes the similar ones of Sullivan and Ferreira-Pinto for 1-dimensional expanding dynamics and also a result of Ferreira-Pinto for 2-dimensional hyperbolic dynamics.