Abstract
The precise production of 4.5 µm off-axis first order FBG in an SMF-28e fiber through femtosecond laser direct writing is demonstrated. The off-axis FBG potential as sensing head for torsion sensing was successfully explored. © 2021 The Author(s).

Abstract
The increase of renewable energy sources of intermittent nature has brought several new challenges for power and energy systems. In order to deal with the variability from the generation side, there is the need to balance it by managing consumption appropriately. Forecasting energy consumption becomes, therefore, more relevant than ever. This paper presents and compares three different ensemble learning methods, namely random forests, gradient boosted regression trees and Adaboost. Hour-ahead electricity load forecasts are presented for the building N of GECAD at ISEP campus. The performance of the forecasting models is assessed, and results show that the Adaboost model is superior to the other considered models for the one-hour ahead forecasts. The results of this study compared to previous works indicates that ensemble learning methods are a viable choice for short-term load forecast. © 2020, Springer Nature Switzerland AG.

Abstract
Over the years, workers have joined in producer organizations to face the difficulties that the capitalist market poses to them. Together they can gain efficiency and equity compared to big companies, and they can gain bargaining power over the product market. In our case, we target smallholder farmers who face many difficulties in increasing their welfare. To overcome them, they group together in producer organizations such as cooperatives. With the development of technology, it became possible for these cooperatives of workers to use the Web to operate - such type of organization and operation is called a Platform Cooperative (PC). This paper presents a multi-agent based modeling of Farmers' Coalition Formation (FCF) for smallholder farmers so that they can operate by means of a Platform cooperative. We present the design of a characteristic function that calculates the coalition values in this context, finds the best way of partitioning the farmers into smaller groups and divides the payoff in a stable manner. We empirically analyze the model using value distributions. The results show that forming coalitions is profitable for farmers. We also proved that the model ensures a fair distribution of the payoff among the farmers.

Abstract
The extraction of collagen from fish skins is being proposed as strategy for valorization of marine origin by-products, being a sustainable alternative to mammal collagen. The method commonly uses solutions of organic acids, but new methodologies are arising, aiming to improve process yields and/or the properties of the resulting products. In this work, skins removed from salt brine Atlantic cod (Gadus morhua) were used to extract collagen, using water acidified with CO2, obtaining an extraction yield of 13.8% (w/w). Acidified water extracted collagen (AWC) presented a total content of proline-like amino acids of 151/1000 residues, with a degree of hydroxylation of 38%, and its SDS-PAGE profile is compatible with type I collagen. Moreover, FTIR, CD and XRD results suggest the presence of preserved triple helix, having a denaturation temperature of 32.3 degrees C as determined by micro-DSC. AWC exhibited a typical shear thinning behavior, interesting regarding their further processing, namely in jelly-like formulations. Additionally, the presence of AWC in MRC-5 human fibroblasts culture did not affect cell viability, demonstrating the non-cytotoxic behavior. Overall, the results support the efficiency of the proposed approach for collagen extraction and further enable the design of methodologies to address AWC use in biomedical or cosmetic context.

Abstract
Residential consumers have been adopting distributed energy resources (DER) like photovoltaics (PV), electric vehicles (EV) as well as electric heating, ventilation and air conditioning devices (HVAC) in recent years - thus substantially reshaping power systems. This study is dedicated to the analysis of such adopters in continental Portugal, using both spatial analysis tools and census data with information theoretic criteria. Results suggest that the current uptake of EV, PV, and HVAC is characterised by spatially auto-correlated adoption patterns. The analysis of census variables, on the other hand, reveals that Portuguese EV, PV, and HVAC adopters exhibit a few surprising, unrecorded characteristics compared with previous studies. Comparing different dataset resolutions, EV and HVAC adopters are found to be most similar across all three aggregation levels considered. Results further show that fewer adopter groups tend to own both EV-HVAC and PV-HVAC, reducing per se synergy potentials that may arise behind the metre. One of the main outcomes from this work is that studies describing energy technology adopters using census variables might receive very unstable results across different data aggregation levels. This may lead to adverse effects on studies' conclusiveness and energy policy design choices.

Abstract
The advances achieved during the last 30 years demonstrate the aptitude of the remote sensing-based vegetation indices (VI) for the assessment of crop evapotranspiration (ETc) and irrigation requirements in a simple, robust and operative manner. The foundation of these methodologies is the well-established relationship between the VIs and the basal crop coefficient (K-cb), resulting from the ability of VIs to measure the radiation absorbed by the vegetation, as the main driver of the evapotranspiration process. In addition, VIs have been related with single crop coefficient (K-c), assuming constant rates of soil evaporation. The direct relationship between VIs and ET is conceptually incorrect due to the effect of the atmospheric demand on this relationship. The rising number of Earth Observation Satellites potentiates a data increase to feed the VI-based methodologies for estimating and mapping either the K-c or K-cb, with improved temporal coverage and spatial resolution. The development of operative platforms, including satellite constellations like Sentinels and drones, usable for the assessment of K-cb through VIs, opens new possibilities and challenges. This work analyzes some of the questions that remain inconclusive at scientific and operational level, including: (i) the diversity of the K-cb-VI relationships defined for different crops, (ii) the integration of K-cb-VI relationships in more complex models such as soil water balance, and (iii) the operational application of K-cb-VI relationships using virtual constellations of space and aerial platforms that allow combining data from two or more sensors.