Abstract

Abstract
This work addresses the joint challenges of layout design and power output smoothing in Airborne Wind Energy farms. The problem is deciding the power units' location and their synchronization, as well as balancing the power output in Airborne Wind Energy Farms, while maximizing the average power output. Airborne Wind Energy systems, particularly the ground-generation type, are susceptible to significant power output fluctuations, which must be mitigated to ensure a stable power flow injected into the electrical grid. We propose and evaluate various synchronization strategies, along with an innovative retraction method introduced in this work, which eliminates the need for synchronized operational cycles among kites. This approach increases flexibility in production cycle selection, leading to a significantly smoother power output signal.

Abstract
The notion of Union is strength is essential for preserving public goods and mitigating public bads such as air quality. International environmental agreements serve this role by forming stable coalitions, in which agents join or leave based on free-riding incentives. Building on the Baliga-Maskin model, we show that such coalitions can emerge from a simple Markov chain mechanism where agents enter or exit through utility-based bargaining. However, stable coalition formation is challenging, as members may receive substantially lower utility than free-riders. This asymmetry gives rise to Barrett's paradox of cooperation: even with large coalitions and strong preferences among free-riders, overall utility may remain far below that of the grand coalition. Encouragingly, the paradox of cooperation can be resolved when free-riders have sufficiently low preferences.

Abstract
A central issue in price competition with positive network effects is the potential for small price changes to trigger abrupt chain reactions, leading to market tipping, winner-take-all scenarios, and zero-profit equilibria. We show that in a duopoly where consumers are not anonymous but partitioned into at least two groups, a simple group-based network structure can, by itself, generate downward-sloping demand and support profitable shared-market equilibria. These are subgame-perfect pure price equilibria in which both firms earn strictly positive profit. Triggering a bandwagon effect and tipping the market remains possible, but requires aggressive price deviations, or price shocks, that produce demand jumps. However, this is not always profitable, and the fear of bankruptcy can be sufficient to stabilize firms in equilibrium. The result relies on having one group with centripetal influence (stronger impact on peers) and another with centrifugal influence (stronger impact on outsiders). It requires no additional sources of heterogeneity or product differentiation. This mechanism shows that positive network effects - when group structured - can endogenously generate stability in price competition. The analysis reconciles the coexistence of local stability and the potential for tipping, offering a unified explanation of how markets with strong network effects can sustain both competition and profitability. We draw a parallel to Turing's reaction-diffusion patterns and reinterpret Becker's intuition that social influence can produce stable outcomes, even when demand may exhibit upward-sloping segments.

Abstract
This study aims to understand the EU countries progress towards the Europe 2030 sustainable development goals (SDGs) in the areas of good health and well-being, gender equality and reduction of inequalities. Data for some indicators related to these areas were collected from the Eurostat database for the period 2010-2023. In order to analyze this three-way data, we first carried out a preliminary analysis through some graphical representations of the data, and then, we used a method of multivariate data analysis, Double Principal Component Analysis, which allows to identify which countries and/or indicators are close to or quite far from the targets. © 2026 Author(s).

Abstract
We address a classification problem where data are not single-valued, but distributions. The objective is to identify Internet traffic re-direction. Each observation consists of a block of 10 measurements of round-trip-times (RTT) measured at each of a set of probes, and is represented by the corresponding empirical distribution. The proposed approach relies on a method for discriminant analysis of distributional data that uses fractional programming, and where distributions are represented by quantile functions, under specific assumptions. A linear discriminant function is defined, that allows obtaining a score for each unit, in the form of a quantile function. This is then used to classify the units in a priori groups, using the Mallows distance. Results show that proposed approach works well, allowing for the identification of the diverted traffic.