Abstract
Agriculture being an essential activity sector for the survival and prosperity of humanity, it is fundamental to use sustainable technologies in this field. With this in mind, some statistical data are analyzed regarding the food price rise and sustainable development indicators, with a special focus on the Portugal region. It is determined that one of the main factors that influences agriculture's success is the soil's characteristics, namely in terms of moisture and nutrients. In this regard, irrigation processes have become indispensable, and their technological management brings countless economic advantages. Like other branches of agriculture, the wine sector needs an adequate concentration of nutrients and moisture in the soil to provide the most efficient results, considering the appropriate and intelligent use of available water and energy resources. Given these facts, the use of renewable energies is a very important aspect of this study, which also synthesizes the main irrigation methods and examines the importance of evaluating the evapotranspiration of crops. Furthermore, the control of irrigation processes and the implementation of optimization and resource management models are of utmost importance to allow maximum efficiency and sustainability in this field.

Abstract
The member states of the European Union (EU) are actively reassessing their National Energy and Climate Plans (NECPs) [1] to jointly address climate challenges and the impacts of the COVID pandemic and gas supply crisis. This study extends the analyses described in [2] by assessing the impact of the updated NECP drafts for Portugal and Spain [3], [4] on the Iberian Electricity Market (MIBEL). For this, we use CEVESA, a market model for the long-term planning and operation of MIBEL that computes the joint dispatch of energy and secondary reserve of the two interconnected single-price zones. Departing from the expected evolution of the electricity generation technologies and demand available in the NECP drafts, joint scenarios for Portugal and Spain are built with the latest CO2 allowances and fuel prices projections and the latest available historical data of hydro and renewable generation profiles. Simulations provide estimates for the expected market prices, technology generation dispatch, and the usage of the capacity of the interconnection lines between both countries, highlighting potential concerns and knowledge on future NECPs.

Abstract
This article presents the prototyping of an educational manipulator robot, based on the "EEZYbotARM Mk2"robot, tailored for first-year master's students in the field of robotics. The project encompasses the assembly of the robot arm, computation of both forward and inverse kinematics, and analysis of two path-planning movement algorithms. These features are consolidated into an Arduino library to streamline the process for students to generate instructions for the robot. The "EEZYbotARM Mk2"features a three-degree-of-freedom revolute arm with a gripper that remains parallel to its base at all times, enhancing its suitability for educational applications such as pick-and-place tasks. The article provides detailed descriptions of the materials and methods employed, along with proposed challenges for student engagement.

Abstract
Lately, the field of optical computing resurfaced with the demonstration of a series of novel photonic neuromorphic schemes for autonomous and inline data processing promising parallel and light-speed computing. We emphasize the Photonic Extreme Learning Machine (PELM) as a versatile configuration exploring the randomness of optical media and device production to bypass the training of the hidden layer. Nevertheless, the implementation of this framework is limited to having the output layer performed digitally. In this work, we extend the general PELM implementation to an all-optical configuration by exploring the amplitude modulation from a spatial light modulator (SLM) as an output linear layer with the main challenge residing in the training of the output weights. The proposed solution explores the package pyTorch to train a digital twin using gradient descent back-propagation. The trained model is then transposed to the SLM performing the linear output layer. We showcase this methodology by solving a two-class classification problem where the total intensity reaching the camera predicts the class of the input sample.

Abstract

Abstract
The educational metaverse promises fulfilling ambitions of immersive learning, leveraging technology-based presence alongside narrative and/or challenge-based deep mental absorption. Most reviews of immersive learning research were outcomes-focused, few considered the educational practices and strategies. These are necessary to provide theoretical and pedagogical frameworks to situate outcomes within a context where technology is in concert with educational approaches. We sought a broader perspective of the practices and strategies used in immersive learning environments, and conducted a mapping survey of reviews, identifying 47 studies. Extracted accounts of educational practices and strategies under thematic analysis yielded 45 strategies and 21 practices, visualized as a network clustered by conceptual proximity. Resulting clusters Active context, Collaboration, Engagement and Scaffolding, Presence, and Real and virtual multimedia learning expose the richness of practices and strategies within the field. The visualization maps the field, supporting decision-making when combining practices and strategies for using the metaverse in education, highlights which practices and strategies are supported by the literature, and the presence and absence of diversity within clusters.