Abstract
Transmission Expansion Planning (TEP) is an optimization problem that has a non-convex and combinatorial search space so that several solution algorithms may converge to local optima. Therefore, many works have been proposed to solve the TEP problem considering its relaxation or reducing its search space. In any case, relaxation and reduction approaches should not compromise the quality of the final solution. This paper aims at analyzing the performance of a search space technique using a Constructive Heuristic Algorithm (CHA) admitting that the TEP problem is then solved using a Discreet Evolutionary Particle Swarm Optimization (DEPSO). On one hand the reduction quality is performed by analyzing whether the optimal expansion routes are included in the CHA constrained set and, on the other hand, the relaxation quality of the DC model is analyzed by checking if the optimal solution obtained with it violates any constraint using the AC model. The simulations were performed using three different test systems. The results suggest that the proposed CHA provides very good results in reducing the TEP search space and that the adoption of the DC model originates several violations if the full AC model is used to model the operation of the power system.

Abstract
One of the main constraints for Renewable Energy Sources (RES) integration in LV networks are overvoltages caused by changing the normal power flow of the network. In favourable weather conditions high voltages may lead to overvoltage trips thus preventing the injection of renewable energy into the grid. An optimized management of power injection from controlled RES to keep the grid voltage within regulatory limits enables a larger energy output and deployment of distributed generation. The SuSTAINABLE project developed a centralized algorithm based on a hierarchical methodology to control distributed power injection and solve the identified issue. A decentralized algorithm based on a coordinated droop control embedded in the inverters was developed as well. In order to evaluate the proposed algorithms a controllable PV µG and batteries were installed at the end of the feeder of a real LV network operated by EDP Distribuicao. The obtained results are presented in this paper and show that a hierarchical methodology to control power injection could optimize RES energy production while maintaining voltages within bounds, thus enabling a larger deployment of RES at the LV levels.

Abstract
Solving nesting problems involves the waste minimisation in cutting processes, and therefore it is not only economically relevant for many industries but has also an important environmental impact, as the raw materials that are cut are usually a natural resource. However, very few exact approaches have been proposed in the literature for the nesting problem (also known as irregular packing problem), and the majority of the known approaches are heuristic algorithms, leading to suboptimal solutions. The few mathematical programming models known for this problem can be divided into discrete and continuous models, based on how the placement coordinates of the pieces to be cut are dealt with. In this paper, we propose an innovative semi-continuous mixed-integer programming model for two-dimensional cutting and packing problems with irregular shaped pieces. The model aims to exploit the advantages of the two previous classes of approaches and discretises the [GRAPHICS] -axis while keeping the [GRAPHICS] -coordinate continuous. The board can therefore be seen as a set of stripes. Computational results show that the model, when solved by a commercial solver, can deal with large problems and determine the optimal solution for smaller instances, but as it happens with discrete models, the optimal solution value depends on the discretisation step that is used.

Abstract
The IEC 61499 standard proposes an event driven execution model for component based (in terms of Function Blocks), distributed industrial automation applications. However, the standard provides only an informal execution semantics, thus in consequence behavior and correctness relies on the design decisions made by the tool vendor. In this paper we present the formalization of a subset of the IEC 61499 standard in order to provide an underpinning for the static verification of Function Block models by means of deductive reasoning. Specifically, we contribute by addressing verification at the component, algorithm, and ECC levels. From Function Block descriptions, enriched with formal contracts, we show that correctness of component compositions, as well as functional and transitional behavior can be ensured. Feasibility of the approach is demonstrated by manually encoding a set of representative use-cases in WhyML, for which the verification conditions are automatically derived (through the Why3 platform) and discharged (using automatic SMT-based solvers). Furthermore, we discuss opportunities and challenges towards deriving certified executables for IEC 61499 models. © 2016 IEEE.

Abstract
One of the major changes currently involving distribution network systems (DNSs) is the ever-increasing integration of renewable-based distributed generation (DG), wind and solar PV types in particular. This is dramatically influencing the planning and operation of distribution systems, in general. The traditional "fit-and-forget" approach is outdated. Current developments in the DNS would require new, efficient and robust planning and operation tools to support smooth integration of such DGs. The present work focuses on an optimal integration of renewable-based DGs with reactive power support capabilities. Accordingly, a stochastic mixed integer linear programming (S-MILP) model is developed that takes into account the optimal integration of RES-based DGs and reactive power sources. The developed model is tested using a standard IEEE distribution system. Test results show that integrating DGs with reactive power support capability significantly enhances voltage stability and improves the overall cost in the system. Simulation results show that setting the reactive power support capability of the RES-based DGs from 0.95 leading to 0.95 lagging leads to the maximum penetration level of wind and solar PV power in the system.

Abstract
Optical immersion clearing is a technique that has been widely studied for more than two decades and that is used to originate a temporary transparency effect in biological tissues. If applied in cooperation with clinical methods it provides optimization of diagnosis and treatment procedures. This technique turns biological tissues more transparent through two main mechanisms - tissue dehydration and refractive index (RI) matching between tissue components. Such matching is obtained by partial replacement of interstitial water by a biocompatible agent that presents higher RI and it can be completely reversible by natural rehydration in vivo or by assisted rehydration in ex vivo tissues. Experimental data to characterize and discriminate between the two mechanisms and to find new ones are necessary. Using a simple method, based on collimated transmittance and thickness measurements made from muscle samples under treatment, we have estimated the diffusion properties of glucose, ethylene glycol (EG) and water that were used to perform such characterization and discrimination. Comparing these properties with data from literature that characterize their diffusion in water we have observed that muscle cell membrane permeability limits agent and water diffusion in the muscle. The same experimental data has allowed to calculate the optical clearing (OC) efficiency and make an interpretation of the internal changes that occurred in muscle during the treatments. The same methodology can now be used to perform similar studies with other agents and in other tissues in order to solve engineering problems at design of inexpensive and robust technologies for a considerable improvement of optical tomographic techniques with better contrast and in-depth imaging.