Abstract
The importance of energy storage continues to grow, whether in power generation, consumer electronics, aviation, or other systems. Therefore, energy management in batteries is becoming an increasingly crucial aspect of optimizing the overall system and must be done properly. Very few works have been found in the literature proposing the implementation of algorithms such as Extended Kalman Filter (EKF) to predict the State of Charge (SOC) in small systems such as mobile robots, where in some applications the computational power is severely lacking. To this end, this work proposes an implementation of the two algorithms mainly reported in the literature for SOC estimation, in an ATMEGA328P microcontroller-based BMS. This embedded system is designed taking into consideration the criteria already defined for such a system and adding the aspect of flexibility and ease of implementation with an average error of 5% and an energy efficiency of 94%. One of the implemented algorithms performs the prediction while the other will be responsible for the monitoring.

Abstract
The present paper seeks to address a gap in the literature regarding green marketing and examines the relationship between ecological concern, inward and outward environmental attitudes, purchasing behavior and environmental behavior as antecedents of green purchasing behavior. The data was gathered through an online survey carried out in Portugal with 530 valid answers. Structural Equation Modelling Partial Least Squares (SEM-PLS) was used to evaluate the model. A t-test was applied to identify differences between men and women. The results show that ecological concern, environmental attitude, environmental behavior and purchase intention are good predictors of green purchase behavior. Women scored higher than men on all variables, meaning that they are indeed superior environmentalists than men. Green purchase behavior is strongly influenced by both purchase intention and environmental behavior, so green brands should focus on targeting individuals that already take some actions in what concerns the environment, or to those who intend to do so.

Abstract
Field-grown grapevines are often exposed to multiple environmental stresses, which challenges wine-growers to develop sustainable measures to sustain vine growth, yield, and quality. Under field conditions this task is demanding, due to differences in the magnitudes of stresses and associated plant responses. In this study we explored the hypothesis that kaolin-particle film application improves grapevine photoprotection through the regulation of xanthophyll cycle genes, limiting the thermal dissipation of excess energy under harsh environmental conditions. Hence, we selected two grapevine varieties, Touriga-Nacional (TN) and Touriga-Franca (TF), grown in the Douro Demarcated Region, and evaluated changes in light dissipation mechanisms, xanthophyll cycle components, and the expression of xanthophyll cycle genes during the 2017 summer season. The results showed that, from veraison to ripening, kaolin triggered the up-regulation of violaxanthin de-epoxidase (VvVDE1) and zeaxanthin epoxidase (VvZEP1) genes, indicating optimised regulation of the xanthophyll cycle. Kaolin treatment also decreased chlorophyll (Chla, Chlb, Chl(a+b)) and carotenoid (Car) accumulation under increasing summer stress conditions in both varieties and lowered the non-photochemical quenching (NPQ) of grapevines on ripening, suggesting a long-term response to summer stress. In addition, kaolin-treated grapevines showed increased Chla/Chlb and lower Chl(a+b)/Car ratios, displaying some features of high light adapted leaves. Overall, this study suggests that kaolin application enabled grapevines to benefit from fluctuating periods of summer stress by managing chlorophyll and carotenoid content and limiting down-regulation of both photochemistry and photoinhibition processes. Under Mediterranean field conditions, kaolin application can be considered an efficient method of minimising summer stress impact on grapevines.

Abstract
Although the literature on crisis communication is quite vast, business communication related to global crises (e.g., natural disasters) is largely unexplored. This chapter aims to fill this gap and shed light on brand communication strategies during a pandemic. A netnographic study was carried out with the purpose of identifying brand positioning and communication strategies during the COVID-19 pandemic outbreak and of understanding the engagement of brands' followers during that period. The study included four brands of large Brazilian companies and comprised the analysis of brands' feed on Instagram during the first five weeks of the outbreak in Brazil. Findings enable to identify two distinct profiles: unprepared brands and leading brands. The chapter provides valuable clues for both managers and researchers dealing with crisis communication.

Abstract
Smart grid (SG) technologies are playing a key role in the electric grid transformation, bringing out promising benefits for different actors and empowering customers. However, this transition imposes new challenges concerning the operation and management of energy, particularly at the distribution level of the electric grid. This chapter provides an overview of achieved advances toward the widespread implementation of SG, including technological and infrastructure developments. Transactive energy presents a distributed decision-making coordination approach using automated energy transactions that is enabled by the intelligence and connectivity benefits of SG. The way in which these transactions can be integrated in a local market environment and how advances in transactive energy, supported by the infrastructure already developed to enable SG, are leading to the emergence of local energy markets is discussed in this chapter. © 2021 Elsevier Inc.

Abstract
Materials represented by measured BRDF (Bidirectional Reflectance Distribution function) with reflectance data captured from real-world materials have become increasingly prevalent due to the development of novel measurement approaches. Nowadays, important limitations can be highlighted in the current material scanning process, mostly related to the high diversity of existing materials in the real-world and the tedious process for material scanning. Consequently, new approaches are required both for the automatic material acquisition process and for the generation of measured material databases. In this study, a novel approach is proposed for modelling the material appearance by sampling hyperspectral measurements on the BRDF domain. An unmanned aerial vehicle (UAV)-based hyperspectral sensor was used to capture high spatial and spectral resolution data. The generated hyperspectral data cubes were used to identify materials with a similar spectral behaviour. Then, a sparse mapping of collected samples is developed to study the appearance of natural and artificial materials in an urban scenario. © 2021 IEEE.