Abstract
Part of the optical clearing study in biological tissues concerns the determination of the diffusion characteristics of water and optical clearing agents in the subject tissue. Such information is sufficient to characterize the time dependence of the optical clearing mechanisms-tissue dehydration and refractive index (RI) matching. We have used a simple method based on collimated optical transmittance measurements made from muscle samples under treatment with aqueous solutions containing different concentrations of ethylene glycol (EG), to determine the diffusion time values of water and EG in skeletal muscle. By representing the estimated mean diffusion time values from each treatment as a function of agent concentration in solution, we could identify the real diffusion times for water and agent. These values allowed for the calculation of the correspondent diffusion coefficients for those fluids. With these results, we have demonstrated that the dehydration mechanism is the one that dominates optical clearing in the first minute of treatment, while the RI matching takes over the optical clearing operations after that and remains for a longer time of treatment up to about 10 min, as we could see for EG and thin tissue samples of 0.5 mm. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

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Abstract

Abstract
This paper presents a modified negative selection algorithm for the diagnosis of disturbance in distribution electrical systems. This study analyzes voltage disturbances and high-impedance faults, based on three phase current and voltage electric measures, which are obtained at the substations. The principal application is to support operation decision aid during faults, as well as to supervise the protection system. To evaluate the performance of the proposed method, simulations were executed using the EMTP software for a distribution test system containing 134 bus. The results obtained were compared with the specialized literature.

Abstract
Production and distribution problems with perishable goods are common in many industries. For the sake of the competitiveness of the companies, the supply chain planning of products with restricted lifespan should be addressed with an integrated approach. Particularly, at the operational level, the sizing and scheduling of production lots have to be decided together with vehicle routing decisions to satisfy the customers. However, such joint decisions make the problems hard to solve for industries with a large product portfolio. This paper proposes an adaptive large neighbourhood search (ALNS) framework to tackle the problem. This metaheuristic is well known to be effective for vehicle routing problems. The proposed approach relies on mixed-integer linear programming models and tools. The ALNS outperforms traditional procedures of the literature, namely, exact methods and fix-and-optimize, in terms of quality of the solution and computational time of the algorithms. Nine in ten runs of ALNS yielded better solutions than traditional procedures, outperforming on average 12.7% over the best solutions provided by the latter methods.

Abstract
This paper presents an algorithm capable of generating smooth, feasible paths for an any-shape non-holonomic mobile robot, taking into account orientation restrictions, with the aim of navigating close to obstacles. Our contribution consists in an extension of the A* algorithm in a cell decomposition, where besides its position, the orientation of the platform is also considered when searching for a path. This is achieved by constructing 16 layers of orientations and only visiting neighbor layers when searching for the lowest cost. To simplify collision checking, the robot's footprint is used to inflate obstacles, yet, to allow the robot to find paths close to obstacles, the actual footprint of the robot must used. By discretizing the orientation space into layers and computing an oriented footprint for each layer, the actual footprint of the robot is used, increasing the configuration space without becoming computationally expensive. The path planning algorithm was developed under the EU-funded project CARLoS(1) and was implemented in a stud welding robot simulated within a naval industry environment, validating our approach.