Abstract
The self-localization of mobile robots in the environment is one of the most fundamental problems in the robotics navigation field. It is a complex and challenging problem due to the high requirements of autonomous mobile vehicles, particularly with regard to the algorithms accuracy, robustness and computational efficiency. In this paper, we present a comparison of three of the most used map-matching algorithms applied in localization based on natural landmarks: our implementation of the Perfect Match (PM) and the Point Cloud Library (PCL) implementation of the Iterative Closest Point (ICP) and the Normal Distribution Transform (NDT). For the purpose of this comparison we have considered a set of representative metrics, such as pose estimation accuracy, computational efficiency, convergence speed, maximum admissible initialization error and robustness to the presence of outliers in the robots sensors data. The test results were retrieved using our ROS natural landmark public dataset, containing several tests with simulated and real sensor data. The performance and robustness of the Perfect Match is highlighted throughout this article and is of paramount importance for real-time embedded systems with limited computing power that require accurate pose estimation and fast reaction times for high speed navigation. Moreover, we added to PCL a new algorithm for performing correspondence estimation using lookup tables that was inspired by the PM approach to solve this problem. This new method for computing the closest map point to a given sensor reading proved to be 40 to 60 times faster than the existing k-d tree approach in PCL and allowed the Iterative Closest Point algorithm to perform point cloud registration 5 to 9 times faster.

Abstract
The importance of planktonic microbial communities is well acknowledged, since they are fundamental for several natural processes of aquatic ecosystems. Microorganisms naturally control the flux of nutrients, and also degrade and recycle anthropogenic organic and inorganic contaminants. Nevertheless, climate change effects and/or the runoff of nutrients/pollutants can affect the equilibrium of natural microbial communities influencing the occurrence of microbial pathogens and/or microbial toxin producers, which can compromise ecosystem environmental status. Therefore, improved microbial plankton monitoring is essential to better understand how these communities respond to environmental shifts. The study of marine microbial communities typically involves highly cost and time-consuming sampling procedures, which can limit the frequency of sampling and data availability. In this context, we developed and validated an in situ autonomous biosampler (IS-ABS) able to collect/concentrate in situ planktonic communities of different size fractions (targeting prokaryotes and unicellular eukaryotes) for posterior genomic, metagenomic, and/or transcriptomic analysis at a home laboratory. The IS-ABS field prototype is a small size and compact system able to operate up to 150 m depth. Water is pumped by a micropump (TCS MG2000) through a hydraulic circuit that allows in situ filtration of environmental water in one or more Sterivex filters placed in a filter cartridge. The IS-ABS also includes an application to program sampling definitions, allowing pre-setting configuration of the sampling. The efficiency of the IS-ABS was tested against traditional laboratory filtration standardized protocols. Results showed a good performance in terms of DNA recovery, as well as prokaryotic (16S rDNA) and eukaryotic (18S rDNA) community diversity analysis, using either methodologies. The IS-ABS automates the process of collecting environmental DNA, and is suitable for integration in water observation systems, what will contribute to substantially increase biological surveillances. Also, the use of highly sensitive genomic approaches allows a further study of the diversity and functions of whole or specific microbial communities.

Abstract
Enhanced utilization of the existing transmission grid is a cheaper and paramount way to have a high penetration of large-scale wind energy resources. Smart wire devices (SWDs) are a new technology to enhance the transfer capability through power flow control. The SWDs are distributed, cheap, self-governing smart assets of FACTS technologies, which can adjust the power flow in an interconnected transmission network. Accordingly, this paper presents a comprehensive three-stage robust SWD placement model, which minimizes the generation and investment costs while guaranteeing that the adaptive and secure robust solution is accustomed to cover the wind uncertainty interval. Since the proposed robust model is not solvable via an off-the-shelf optimization package and to reduce the computation burden of the solution process, an effective solution strategy is proposed to solve it. Detailed simulation results on the IEEE 24-bus system verify the effectiveness of the proposed robust SWD placement model.

Abstract
A Fabry-Perot interferometer was fabricated inside a fused silica substrate through femtosecond laser micromachining. The influence of the waveguide's writing parameters on the measured signal's quality was studied for an interferometer with a 27-mu m wide cavity. Optimal signal-to-noise ratio and fringe visibility were obtained for waveguides written at 75 nJ and 50 mu m/s. The same device was characterized with different refractive index liquids, and a maximum sensitivity of 1181.4 +/- 23.6 nm/RIU was obtained in the index range of 1.2962 to 1.3828 (at 1550 nm) for the spectral order m = 46.

Abstract
Many Generation Expansion Problems (GEP) models have been proposed in the literature based on agent-based equilibria or cost-minimization, integrated in bilevel or single-level models. In the simplest (and unrealistic) single-level cost minimization GEP with only the balance constraint, it can be proved that optimal generation investments are recovered through the system marginal cost, meaning that the Net Present Value (NPV) is 0. However, in more complex representations with additional constraints (such as technical or minimum capacity system constraints) non-profitable investments might occur, i.e., their NPV can go below 0. The aim of this work is to provide insights on how introducing complexity into GEP models affects the investments with and without imposing positive NPV as new constraints. The non-linearities in the NPV formulation are solved with a novel iterative algorithm. The main conclusion from the case studies is that the cost minimization GEP model forcing positive NPV can help to better represent the behavior of energy market players and simulate oligopolistic energy markets without explicitly representing profit maximization.

Abstract
This paper describes an open standards-based information system that can support the democratization and consumer empowerment through flexibility activation in the distribution networks of the near future. The paper outlines a software infrastructure focused on technical issues, closely following the OpenADR standard and the corresponding IEC 62746-10 standard. The infrastructure represents a communication backbone allowing the connection, registering, activation and reporting for different types of granular consumer flexibility. The flexibility sources can be very diverse - from controllable charging set points of electric vehicle chargers and district-level storages such as stationary batteries, towards taking advantage of comparatively large time constants of thermal systems in residential and commercial buildings. In the viewpoint of the proposed system, all these flexibility provisions represent distributed energy resources in a wider sense. The system thus offers interoperable support for consumer-level integration of different energy systems (electricity, heat and gas), and additional flexibility sources are made available to the electric power system, all the time keeping the user comfort and avoiding service disruptions. The paper outlines the technical infrastructure as a backbone activating new sources of flexibility, helping the further proliferation of renewable energy sources and establishing new market actors.