Finis Terrae University

The transition toward sustainable energy systems is increasing the operational complexity of modern power grids due to the high penetration of renewable energy sources, distributed energy resources, and bidirectional energy flows. Artificial intelligence has emerged as a key enabling technology for forecasting, optimization, and control in smart grids. Current AI implementations in energy systems lack unified workflows integrating forecasting, decision-making, adaptive stability regulation, and distributed coordination. Moreover, existing control approaches rarely incorporate biologically inspired stability mechanisms such as homeostatic regulation, limiting system-level resilience under dynamic operating conditions. This work aims to develop an architectural framework in the form of a unified artificial intelligence meta-pipeline enabling homeostatic control and distributed resource optimization in sustainable energy systems through closed-loop intelligent operation. A layered artificial intelligence meta-pipeline architecture is proposed integrating system representation, data intelligence, decision intelligence, homeostatic feedback regulation, and distributed coordination. A formal Homeostatic Energy Index is introduced to quantify system stress and enable supervisory adaptive policy regulation. The framework is validated using a reproducible microgrid-level simulation combining reinforcement learning-based control with homeostatic feedback regulation. Experimental validation demonstrates stable closed-loop operation under stochastic demand and renewable variability. The framework maintains bounded system stress levels, achieving an average Homeostatic Energy Index of 18.17 while preserving near-zero energy imbalance performance, confirming that homeostatic feedback improves stability without degrading energy balancing performance. This work introduces a unified artificial intelligence meta-pipeline architectural framework and formally defines a homeostatic feedback layer for sustainable energy system control. The proposed approach enables stability-aware structured integration of heterogeneous AI components and provides a foundation for self-adaptive, resilient, and distributed intelligent energy systems.

Conjugated polymers have recently regained strong interest because of their potential in organic electronic devices such as organic light-emitting diodes (OLEDs), field-effect transistors (FETs), and organic photovoltaics (OPVs). Unlike inorganic semiconductors where electrons are commonly treated as delocalized or quasi-free Bloch states,electrons in conjugated polymers occupy strongly coupled, localized sigma and pi orbitals and interact intensely with the ionic lattice. These materials therefore deviate markedly from the assumptions underlying Bloch-based approaches, motivating the development of alternative theoretical descriptions of charge transport. Here we present a many-body model that explicitly includes electron-electron interactions, both on-site and between pi states on alternating chain sites. The model naturally explains semiconducting behavior in the undoped polymer and predicts two novel flat bands of excited bonding states. These excited states exhibit bosonic character and enable an unconventional charge-transport channel. The model also quantitatively reproduces experimental observations, yielding excellent fits to measured UV-Vis absorption and electro-luminescence spectra.

Introduction: The mental health of health sciences students is a growing concern in medical education, given the heavy academic workload and early clinical demands that characterize their training. Objectives: To evaluate the prevalence of symptoms of depression, anxiety, and stress in health sciences students in Chile and to analyze their association with lifestyle factors relevant to the educational process. Methods: An analytical cross-sectional study was conducted with 991 students who, after providing informed consent, completed the DASS-21 (Depression, Anxiety, and Stress Scales), a 21-item self-report questionnaire designed to measure the severity of symptoms of depression, anxiety, and stress. Perceived sleep quality, physical activity, and tobacco use were also analyzed. Descriptive and bivariate analyses were performed, followed by binary logistic regression adjusted for sex and age to identify factors associated with psychological symptoms. The study was approved by a Scientific Ethics Committee. Results: A high prevalence of psychological symptoms was observed, especially anxiety (63.8%) and stress (80.3%), with greater severity in women (p < 0.001). Poor sleep quality was significantly associated with higher levels of depression, anxiety, and stress. Students with poor sleep quality were approximately three times more likely to experience depressive symptoms (AOR = 3.05; 95% CI: 2.30-4.04), stress (AOR = 3.57; 95% CI: 2.48-5.13), and anxiety (AOR = 2.78; 95% CI: 2.10-3.69). Physical activity did not show an independent association in the adjusted models, while tobacco use showed sex-specific associations. Conclusions: A high burden of emotional distress is evident among health sciences students. Sleep quality emerges as a key cross-cutting factor, reinforcing the need to incorporate institutional strategies for promoting sleep and preventing psychological distress within the educational environment.

Abstract Background Overweight and obesity are associated with reduced fertility outcomes in assisted reproduction. This scoping review maps available evidence on pre-IVF weight management interventions. Methods We searched PubMed/MEDLINE (2008–2025) for studies evaluating weight management interventions (dietary, exercise, pharmacological, surgical) before or during IVF in women with BMI ≥ 25 kg/m². We included randomized controlled trials, quasi-experimental studies, and cohorts with interventions. Two reviewers independently screened records and extracted data on interventions and outcomes. Supplementary searches included reference screening and citation tracking. Results From 230 records, 19 studies met inclusion criteria: 17 evaluating IVF-specific outcomes — lifestyle or dietary interventions (n = 10), pharmacological therapies (n = 3), and bariatric surgery (n = 4) — and 2 examining preconception interventions before other ART modalities included exclusively to inform implementation challenges. Weight loss was achieved across intervention categories, though the magnitude varied substantially. Improvements in reproductive outcomes were inconsistent. Some studies reported improved pregnancy rates following lifestyle interventions, while well-designed trials showed no significant differences despite weight reduction. Orlistat showed no reproductive benefit; GLP-1 agonist combination therapy showed preliminary promise in PCOS. Bariatric surgery produced substantial weight loss but inconsistent live birth outcomes. High attrition rates (> 20%), treatment delays, and variable adherence were common challenges. Conclusions Pre-IVF weight management interventions demonstrate substantial outcome heterogeneity. While weight loss is achievable, reproductive benefits are inconsistent. Evidence does not support rigid BMI cutoffs. Clinical decisions should be individualized. Future research should identify predictive factors and optimize intervention protocols.

This study aims to describe the audiovisual representation of immigration as portrayed by the digital community media outlet El Salto TV, and to assess whether it offers a distinctive perspective aligned with its journalistic principles, in contrast to the coverage typically provided by traditional and digital audiovisual media. A mixed-methods longitudinal research design was employed, combining a content analysis of the entire corpus of news pieces on the subject (n=103) published between 2017 and 2024 on both the outlet's website and its social media platforms (Facebook, Instagram, and X), with a semi-structured interview conducted with the head of the audiovisual section. The analysis focused on variables such as sources, audiovisual narrative, scope of coverage, thematic and visual framing, informational treatment, and language. The findings indicate that El Salto TV constructs a counter-narrative on immigration, characterized by granting immigrant communities a central and active role in the news discourse. Moreover, the outlet delivers coverage that reflects its community-based ethos, distinctly different from that of other audiovisual media, thereby contributing to the development of new narrative frameworks and fostering best practices in journalism.