Over the last few years, the interest in the analysis of the energy consumption of Android applications has been increasing significantly. Indeed, there are a considerable number of studies which aim at analyzing the energy consumption in various ways, such as measuring/estimating the energy consumed by an application or block of code, or even detecting energy expensive coding patterns or API's.

Nevertheless, when it comes to actually improving the energy efficiency of an application, we face a whole new challenge, which can only be achieved through source code improvements that can take advantage of energy saving techniques. However, there is still a lack of information about such techniques and their impact on energy consumption.

In this paper, we analyze the impact of the memoization technique in the energy consumption of Android applications. We present a systematic study of the use of memoization, where we compare implementations of 18 method from different applications, with and without using memoization, and measure the energy consumption of both of them. Using this approach, we are able to characterize Android methods that should be memoized.

Our results show that using memoization can clearly be a good approach for saving energy. For the 18 tested methods, 13 of them decreased significantly their energy consumption, while for the remaining 5 we observed unpredictable behavior in 3 of them and an overall increase of energy consumption in the last 2. We also included a discussion about when is actually beneficial to use memoization for saving energy, and what is the expected percentage of gain/loss when memoization works and when it does not.

In this paper we address a wireless network design problem on a railway line. Given a finite set of locations along a railway line and different types of communication antennas that can be installed at each of these locations, which locations and which type of antenna should be selected to ensure a certain level of signal coverage along the railway line while minimizing construction costs? We formulate the problem as a 0/1 linear optimization model, prove that the problem is NP-hard, and report computational experiments using real and simulated data. The computational tests showed that the model is capable of solving the problem for railway lines longer than any existing real railway lines.

The European Metal sector is at a critical juncture, navigating through the complex landscape of the twin transition towards digitalization and sustainability. This transformative journey, though essential, is fraught with challenges that if not addressed, could undermine the sector's resilience, competitiveness and social equity. The Metallica project emerges as a pivotal initiative in this context, aiming to mitigate these challenges by fostering enhanced worker engagement, participation and conflict resolution.

The European Metal sector is at a critical juncture, navigating through the complex landscape of the twin transition towards digitalization and sustainability. This transformative journey, though essential, is fraught with challenges that if not addressed, could undermine the sector's resilience, competitiveness and social equity. The Metallica project emerges as a pivotal initiative in this context, aiming to mitigate these challenges by fostering enhanced worker engagement, participation and conflict resolution.