Abstract
Introduction: Together with sociodemographic and clinical features, locus of control and self-efficacy may impact the processes underlying changes in eating habits. Objectives: To study the relationships of sociodemographic and clinical characteristics, locus of control, general self-efficacy and eating self-efficacy with the perception of adherence to healthy eating among patients undergoing treatment for overweight. Methodology: A convenience sample of 74 overweight (BMI = 25.0 kg/m2) individuals (77.0% females, mean age = 41 years, SD = 11) attending nutrition consultations was studied regarding sociodemographic and clinical data, stages of change towards healthy eating, health locus of control (Health Locus of Control Scale), eating self-efficacy (General Eating Self-Efficacy Scale) and general self-efficacy (Self-Concept Clinical Inventory’s self-efficacy factor). Results: Approximately two-thirds (67.6%) of participants were in the “Action/Maintenance” stage towards healthy eating. In the total locus of control scale, general self-efficacy and eating self-efficacy, participants showed average scores slightly higher than the midpoint of the respective scales. In a binary logistic regression model, sociodemographic, clinical, locus of control and self-efficacy variables significantly predicted being in the action/maintenance stage towards healthy eating (p < 0.001; Nagelkerkle’s R2 = 48.4%). A higher proportion of weight loss (adjusted Exp(ß) = 1.074, p = 0.017) and higher eating self-efficacy (adjusted Exp(ß) = 1.317, p = 0.005) were significantly associated with higher odds of being in the “Action/Maintenance” stage. Conclusions: Most participants attending nutrition consultations to treat overweight considered following a healthy diet. Higher eating self-efficacy and greater weight loss associated to being in the “Action/Maintenance” stage towards healthy eating.

Abstract
The Renewable Energy Communities (RECs) and self-consumption frameworks defined in Directive (EU) 2023/2413 and Directive (EU) 2024/1711 are currently being integrated into national regulations across EU member states, adapting legislation to incorporate these new entities. These regulations establish key principles for individual and collective self-consumption, outlining operational rules such as proximity constraints, electricity sharing mechanisms, surplus electricity management, grid tariffs, and various organizational aspects, including asset sizing, licensing, metering, data exchange, and role definitions. This study introduces a model tailored to optimize investment and energy-sharing decisions within RECs, enabling multiple members to invest in solar photovoltaic (PV) and wind generation assets. The model determines the optimal generation capacity each REC member should install for each technology and calculates the energy shared between members in each period, considering site-specific constraints on renewable deployment. A case study with a four-member REC is used to showcase the model’s functionality, with simulation results underscoring the benefits of CSC over ISC. © 2025 by the authors.

Abstract
Background/Objectives: Obesity is a major contributor to cardiovascular disease, yet traditional risk assessment methods may overlook behavioral and circadian influences that modulate metabolic health. Chronotype, physical activity, sleep quality, eating speed, and breakfast habits have been increasingly associated with cardiometabolic outcomes. This study aims to evaluate the associations between these behavioral factors and both anthropometric and biochemical markers of cardiovascular risk among obese candidates for bariatric surgery. Methods: A cross-sectional study was conducted in a sample of 286 obese adults (78.3% females, mean 44.3 years, SD = 10.8, mean BMI = 42.5 kg/m2, SD = 6.2) followed at a central Portuguese hospital. Chronotype (reduced Morningness-Eveningness Questionnaire), sleep quality (Pittsburgh Sleep Quality Index), physical activity (Godin-Shephard Questionnaire), eating speed, and breakfast skipping were assessed. Cardiovascular risk markers included waist-to-hip ratio (WHR), waist-to-height ratio, A Body Shape Index (ABSI), Body Roundness Index, atherogenic index of plasma (AIP), triglyceride-glucose index (TyG), and homeostatic model assessment for insulin resistance (HOMA-IR). Results: Men exhibited significantly higher WHR, ABSI, HOMA-IR, TyG, and AIP. Eveningness was associated with higher insulin (r = -0.168, p = 0.006) and HOMA-IR (r = -0.156, p = 0.011). Poor sleep quality was associated with higher body fat mass (r = 0.151, p = 0.013), total cholesterol (r = 0.169, p = 0.005) and LDL cholesterol (r = 0.132, p = 0.030). Faster eating speed was associated with a higher waist circumference (r = 0.123, p = 0.038) and skeletal muscle mass (r = 0.160, p = 0.009). Conclusions: Male sex, evening chronotype, and poor sleep quality were associated with more adverse cardiometabolic profiles in individuals with severe obesity. These findings support the integration of behavioral and circadian factors into cardiovascular risk assessment strategies.

Abstract
Magneto-optic surface plasmon resonances (MOSPRs) rely on the interaction of magnetic fields with surface plasmon polaritons (SPP) to modulate plasmonic bands with magnetic fields and enhance magneto-optical activity. In the present work, a study on the magnetoplasmonic behavior of Ag/Fe bilayers is carried out by VIS-NIR spectroscopy and backed with SQUID measurements, determining the thickness-dependent magnetization of thin-film samples. The MOSPR sensing properties of Ag/Fe planar bilayers are simulated using Berreman's matrix formalism, from which an optimized structure composed of 15 nm of Ag and 12.5 nm of Fe is obtained. The selected structure is fabricated and characterized for refractive index (RI) sensitivity, reaching 4946 RIU-1 and returning an effective enhancement of refractometric sensitivity after magneto-optical modulation. A new optimized and cobalt-free magnetoplasmonic Ag/Fe bilayer structure is studied, fabricated, and characterized for the first time towards refractometric sensing, to the best of our knowledge. This configuration exhibits potential for enhancing refractometric sensitivity via magneto-optical modulation, thus paving the way towards a simpler, more accessible, and safe type of RI sensor with potential applications in chemical sensors and biosensors.

Abstract
This paper presents a solution for visualizing oil spills at sea by combining satellite data with virtual choreographies. The system enables dynamic, interactive visualization of oil slicks, reflecting their shape, movement, and interaction with environmental factors like currents and wind. High-resolution geospatial data supports a multiplatform experience with aerial and underwater perspectives. This approach promotes independence, interoperability, and multiplatform compatibility in environmental disaster monitoring. The results validate virtual choreographies as effective tools for immersive exploration and analysis, offering structured data narratives beyond passive visualization - especially valuable for mixed reality applications. © 2025 IEEE.

Abstract
Multivariate time series analysis is a vital but challenging task, with multidisciplinary applicability, tackling the characterization of multiple interconnected variables over time and their dependencies. Traditional methodologies often adapt univariate approaches or rely on assumptions specific to certain domains or problems, presenting limitations. A recent promising alternative is to map multivariate time series into high-level network structures such as multiplex networks, with past work relying on connecting successive time series components with interconnections between contemporary timestamps. In this work, we first define a novel cross-horizontal visibility mapping between lagged timestamps of different time series and then introduce the concept of multilayer horizontal visibility graphs. This allows describing cross-dimension dependencies via inter-layer edges, leveraging the entire structure of multilayer networks. To this end, a novel parameter-free topological measure is proposed and common measures are extended for the multilayer setting. Our approach is general and applicable to any kind of multivariate time series data. We provide an extensive experimental evaluation with both synthetic and real-world datasets. We first explore the proposed methodology and the data properties highlighted by each measure, showing that inter-layer edges based on cross-horizontal visibility preserve more information than previous mappings, while also complementing the information captured by commonly used intra-layer edges. We then illustrate the applicability and validity of our approach in multivariate time series mining tasks, showcasing its potential for enhanced data analysis and insights.