Improving the energy efficiency and reducing the CO$_{2}$emissions are key strategic objectives for governments on an international level. Although children represent the future energy consumers and efforts have been made to enhance their understanding of energy consumption, there is a lack of initiatives focused on assessing children's awareness regarding energy usage at home and school. Serious games present a highly effective approach to educate and raise children's awareness about energy production and consumption; they are widely used to simulate real-world scenarios, inform or raise players' awareness, and stimulate their problem-solving abilities. Moreover, they assist players in visualising their actions and intuitively exploring different events. This article discusses the development of a serious game, theGreenMategame, which visually portrays the daily activities and experiences of a primary school student. It incorporates progressive levels to enhance comprehension and knowledge of the diverse factors influencing the growing energy crisis, as well as strategies for managing and mitigating them. According to our experimental findings, theGreenMategame can be used as a productive educational tool to effectively foster desired changes in children's behavior regarding energy consumption.

Quantifying the amount, content and direction of communication between brain regions is key to understanding brain function. Traditional methods to analyze brain activity based on the Wiener-Granger causality principle quantify the overall information propagated by neural activity between simultaneously recorded brain regions, but do not reveal the information flow about specific features of interest (such as sensory stimuli). Here, we develop a new information theoretic measure termed Feature-specific Information Transfer (FIT), quantifying how much information about a specific feature flows between two regions. FIT merges the Wiener-Granger causality principle with information-content specificity. We first derive FIT and prove analytically its key properties. We then illustrate and test them with simulations of neural activity, demonstrating that FIT identifies, within the total information propagated between regions, the information that is transmitted about specific features. We then analyze three neural datasets obtained with different recording methods, magneto- and electro-encephalography, and spiking activity, to demonstrate the ability of FIT to uncover the content and direction of information flow between brain regions beyond what can be discerned with traditional analytical methods. FIT can improve our understanding of how brain regions communicate by uncovering previously unaddressed feature-specific information flow.

This paper presents Ring Optical Network (RingO), a wavelength-division-multiplexing (WDM), ring-based, optical packet network suitable for a high-capacity metro environment. We present three alternative architectural designs and elaborate on the effectiveness of optic with respect to electronic technologies, trying to identify an optimal mix. We present the design and prototyping of a simple but efficient access control protocol, based upon the equivalence of the proposed network architecture with input-buffering packet switches. We discuss the problem of node allocation to WDM channels, which can be viewed as a particular optical network design problem. We, finally, briefly illustrate the fault protection properties of the RingO architecture. The main contribution of this paper is the identification and experimental validation of an innovative optical network architecture, which is feasible and cost effective with technologies available today, and can be a valid alternative to more consolidated solutions in metro applications.