Abstract
Using the finite element method (FEM), this paper presents a numerical investigation of the performance analysis of a D-type photonic crystal fiber (D-type PCF) for refractive index sensing, based on surface plasmon resonance (SPR) with a planar structure made out of a metamaterial. COMSOL Multiphysics was used to evaluate the design of the referred refractive index optical fiber sensor, with higher accuracy and considerable economy of time and resources. A study of different metamaterials concentrations conformed by aluminum oxide (Al2O3) and silver (Ag) is carried out. Another structural parameters, which influences the refractive index sensor performance, the thickness of the metamaterial, is also investigated. The results indicate that the use of metamaterials provides a way of improving the performance of SPR sensors on optical fibers and allows to tailor the working parameters of the sensor.

Abstract
Near-future electric distribution grids operation will have to rely on demand-side flexibility, both by implementation of demand response strategies and by taking advantage of the intelligent management of increasingly common small-scale energy storage. The Home energy management system (HEMS), installed at low voltage residential clients, will play a crucial role on the flexibility provision to both system operators and market players like aggregators. Modeling and forecasting multi-period flexibility from residential prosumers, such as battery storage and electric water heater, while complying with internal constraints (comfort levels, data privacy) and uncertainty is a complex task. This papers describes a computational method that is capable of efficiently learn and define the feasibility flexibility space from controllable resources connected to a HEMS. An Evolutionary Particle Swarm Optimization (EPSO) algorithm is adopted and reshaped to derive a set of feasible temporal trajectories for the residential net-load, considering storage, flexible appliances, and predefined costumer preferences, as well as load and photovoltaic (PV) forecast uncertainty. A support vector data description (SVDD) algorithm is used to build models capable of classifying feasible and non-feasible HEMS operating trajectories upon request from an optimization/control algorithm operated by a DSO or market player.

Abstract
In this study, hyperspectral reflectance (HySR) data derived from a handheld spectroradiometer were used to assess the water status of three grapevine cultivars in two sub-regions of Douro wine region during two consecutive years. A large set of potential predictors derived from the HySR data were considered for modelling/predicting the predawn leaf water potential (Psi(pd)) through different statistical and machine learning techniques. Three HySR vegetation indices were selected as final predictors for the computation of the models and the in-season time trend was removed from data by using a time predictor. The vegetation indices selected were the Normalized Reflectance Index for the wavelengths 554 nm and 561 nm (NRI554;561), the water index (WI) for the wavelengths 900 nm and 970 nm, and the D1 index which is associated with the rate of reflectance increase in the wavelengths of 706 nm and 730 nm. These vegetation indices covered the green, red edge and the near infrared domains of the electromagnetic spectrum. A large set of state-of-the-art analysis and statistical and machine-learning modelling techniques were tested. Predictive Modelling techniques based on generalized boosted model (GBM), bagged multivariate adaptive regression splines (B-MARS), generalized additive model (GAM), and Bayesian regularized neural networks (BRNN) showed the best performance for predicting Psi(pd), with an average determination coefficient (R-2) ranging between 0.78 and 0.80 and RMSE varying between 0.11 and 0.12 MPa. When cultivar Touriga Nacional was used for training the models and the cultivars Touriga Franca and Tinta Barroca for testing (independent validation), the models performance was good, particularly for GBM (R-2 = 0.85; RMSE = 0.09 MPa). Additionally, the comparison of Psi(pd) observed and predicted showed an equitable dispersion of data from the various cultivars. The results achieved show a good potential of these predictive models based on vegetation indices to support irrigation scheduling in vineyard.

Abstract
In this paper, typical strengths, fault levels, and source impedances are thoroughly analyzed and calculated for the study of quality of supply in 230/400 V 50 Hz distribution systems. Considering all the disparity in distribution network design, this study is based on a comprehensive database containing typical arrangements and equipment in U.K./European systems, as well as on fully documented generic network models supplying four residential load subsectors in the U.K., i.e., from metropolitan to rural areas. Thus, this paper proposes an alternative method for determining reference values of network supply impedances and short-circuit fault levels at different points and locations of the medium-to-low voltage distribution system. The aim of this study is to provide a wider range of benchmark values than those stipulated in the IEC 60725 Standard, which only defines a single-reference threshold of public supply impedances for all types of distribution systems and residential customers. In order to assist network operators in the planning and design of their distribution systems, these values are further disaggregated and classified in this paper according to network/demand type.

Abstract
This paper is an extension of work originally presented at the 2nd International Conference of the Portuguese Society for Engineering Education and aims to describe an interdisciplinarity teaching experiment involving three subjects of the scientific area of Mathematics and a fourth one in the area of Management. Using only one project, the students developed skills, in an integrated way, in the fields of the subjects involved. The structure of the project is described in detail. It is shown how the knowledge obtained in the different subjects is needed and how it connects together to answer the proposed challenges. We report the progress of the students' work, the main difficulties and the skills developed during this process. We conclude with a reflection on the main problems and gains that may arise in similar projects.

Abstract
Long period fiber gratings (LPFGs) were used to monitor the characteristics of copper (Cu) thin films when annealed in air atmosphere up to similar to 680 degrees C. The wavelength and the optical power shift of the resonant bands of the LPFGs when coated with the Cu thin films, were measured as a function of the annealing temperature, and were found to exhibit a different evolution comparing to a bare LPFGs. Thin films of Cu deposited on quartz (SiO2) substrates were annealed and analyzed by XRD, SEM/EDS and Raman spectroscopy, allowing to identify the formation of two distinct oxide phases at different temperatures, cuprous (Cu2O-cuprite) and cupric (CuO-tenorite) oxides, respectively. The observed features of the resonant bands of the LPFGs were found to be associated with the Cu oxide phase transitions, indicating the possibility of using LPFGs to monitor, in real time, the oxidation states of Cu thin films by following specific characteristics of the attenuation bands. In addition, LPFGs over coated with the two distinct oxidation phases of Cu were characterized for refractive index sensing in the range between 1.300 to 1.600, leading to the conclusion that the sensitivity to the refractive index of the surrounding medium of Cu coated LPFGs sensing systems can be temperature tuned.