Abstract
Purpose: To study the impact of shielding elements in the proximity of Intra-Operative Radiation Therapy (IORT) irradiation fields, and to generate graphical and quantitative information to assist radiation oncologists in the design of optimal shielding during pelvic and abdominal IORT. Method: An IORT system was modeled with BEAMnrc and EGS++ Monte Carlo codes. The model was validated in reference conditions by gamma index analysis against an experimental data set of different beam energies, applicator diameters, and bevel angles. The reliability of the IORT model was further tested considering shielding layers inserted in the radiation beam. Further simulations were performed introducing a bone-like layer embedded in the water phantom. The dose distributions were calculated as 3D dose maps. Results: The analysis of the resulting 2D dose maps parallel to the clinical axis shows that the bevel angle of the applicator and its position relative to the shielding have a major influence on the dose distribution. When insufficient shielding is used, a hotspot nearby the shield appears near the surface. At greater depths, lateral scatter limits the dose reduction attainable with shielding, although the presence of bone-like structures in the phantom reduces the impact of this effect. Conclusions: Dose distributions in shielded IORT procedures are affected by distinct contributions when considering the regions near the shielding and deeper in tissue: insufficient shielding may lead to residual dose and hotspots, and the scattering effects may enlarge the beam in depth. These effects must be carefully considered when planning an IORT treatment with shielding.

Abstract
A curvature sensor based on an Fabry-Perot (FP) interferometer was proposed. A capillary silica tube was fusion spliced between two single mode fibers, producing an FP cavity. Two FP sensors with different cavity lengths were developed and subjected to curvature and temperature. The FP sensor with longer cavity showed three distinct operating regions for the curvature measurement. Namely, a linear response was shown for an intermediate curvature radius range, presenting a maximum sensitivity of 68.52 pm/m(-1). When subjected to temperature, the sensing head produced a similar response for different curvature radii, with a sensitivity varying from 0.84 pm/degrees C to 0.89 pm/degrees C, which resulted in a small cross-sensitivity to temperature when the FP sensor was subjected to curvature. The FP cavity with shorter length presented low sensitivity to curvature.

Abstract
In this paper, we propose and experimentally investigate an optical sensor based on a novel combination of a long-period fiber grating (LPFG) with a permanent magnet to measure electrical current in unmanned aerial vehicles (UAVs). The proposed device uses a neodymium magnet attached to the grating structure, which suffers from an electromagnetic force produced when the current flows in the wire of the UAV engine. Therefore, it causes deformation on the sensor and thus, different shifts occur in the resonant bands of the transmission spectrum of the LPFG. Finally, the results show that it is possible to monitor electrical current throughout the entire operating range of the UAV engine from 0 A to 10 A in an effective and practical way with good linearity, reliability and response time, which are desirable characteristics in electrical current sensing. © 2016 by the authors; licensee MDPI, Basel, Switzerland.

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.