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Families of young people who self-harm: a mixed-methods systematic review of their experiences and needs
Publication . Cação-Dias, Beatriz; Rothes, Inês; Carmo, Cláudia; Nunes, Cristina; Brás, Marta
Background: Self-harm in young people is a pressing public health issue, with family support playing a crucial role in the young per son’s prognosis. Concurrently, the impact extends to families themselves, who must navigate caregiving responsibilities while also requiring support. Understanding these experiences is key to providing more effective assistance in their caregiving roles. Aim: With this mixed-methods systematic review we investigated the experiences, barriers, and needs of families of young people who self-harm. Method: Following PRISMA guidelines, a search was conducted within PsycINFO, PubMed, Web of Science, and Scopus databases in July 2024 and April 2025. Thirty-one studies were included in this review, and quality was assessed with the Mixed Methods Appraisal Tool (MMAT). A narrative synthesis was employed for the quantitative data, while qualitative data were analyzed with thematic synthesis. Results: The quantitative findings revealed two themes: (1) the repercussions of self-harm in the family and (2) family support needs. Qualitative analysis identified four themes: (1) parents’ emotional and psychological impact; (2) impact on parenting and the bond with the young person; (3) disruption of family dynamics; and (4) barriers to and pathways for family support. Conclusion: We discuss the implications of these findings, offering recommendations for future research and improvements in family support services to alleviate caregiver burden and foster supportive environments for recovery.
Digital twin modelling for a renewable energy community: a case study of the culatra island’s smart grid
Publication . Ogunsola, Idris Olalekan; Santos, Joni; Monteiro, Jânio; Pacheco, André
This study develops and tests a Digital Twin (DT) of the Culatra Island’s distribution grid to enable the evaluation of demand side management strategies, in the scope of Renewable Energy Communities. Built in MATLAB/Simulink and structured across five functional layers, the DT integrates real-world data from five photovoltaic (PV) production units, monitored and fixed electrical loads, and realistic network parameters derived from the island’s infrastructure. Three steady-state test scenarios were simulated to assess voltage stability, and power flow under: 1) baseline grid operation without PV generation, 2) distributed PV integration under normal load conditions, and 3) high-demand operation near generationload equilibrium. Results show that PV integration improves voltage regulation and reduces losses through localized energy injection and bidirectional power flow. However, under peak load conditions, the system exhibits significant undervoltage, revealing the need for advanced control strategies and infrastructure reinforcement. Overall, the DT proves to be an effective analytical and decision-support tool for optimising distributed energy systems. This work provides a replicable application-oriented framework for data-driven planning in emerging Renewable Energy Communities and supports Culatra Island’s transition toward full energy self-sufficiency. Unlike prior studies that report generalized benefits of PV integration, this work explicitly identifies voltage instability thresholds under high-demand conditions in a real REC configuration, providing actionable insight into when passive operation becomes insufficient.
The effects of country governance quality on corporate sustainability and ethical behaviour
Publication . Francisco, Paulo Morais
Using institutional theory, we examine how country governance affects two ESG outcomes: ESG performance and ESG controversies. With Refinitiv/LSEG data for ~146,000 firm‐years in 86 countries (2002–2023) and World Bank WGI, we apply a Mundlak within/between decomposition to test complementarity versus substitution (performance) and prevention versus detection (controversies). Better governance is strongly associated with higher ESG performance—overall and across E, S and G—especially cross‐country. Yet governance also predicts more reported controversies, consistent with detection/visibility rather than worse conduct. Instrumental Variable and DiD tests corroborate these results. JEL Classification: D02, M14, Q56, C23
Comparative proteomic analysis of trioza erytreae nymphs developed on Citrus ×limon and Citrus ×sinensis host plants
Publication . Magalhães, Tomás Thormann Abranches de; Anjos Guerreiro, Liliana Isabel Tomé; Power, Deborah Mary; Pereira, José Alberto Cardoso; Duarte, Amilcar; Tomás Marques, Natália
Trioza erytreae is a vector of Huanglongbing (HLB), a highly damaging citrus disease. Lemon plants (Citrus ×limon) are the preferred host for T. erytreae, although the underlying mechanisms behind this remain to be fully elucidated. A comparative proteomic analysis of T. erytreae nymphs in their fourth and fifth instars that were fed either lemon or sweet orange (SwO) was carried out to investigate the interaction with its hosts. A 24-hour sucrose feeding assay was conducted to understand proteomic responses to a nutrient-poor diet. Proteomic profiling using nanoscale liquid chromatography coupled to tandem mass spectrometry (nanoLC-MS/MS) identified a total of 1,477 psyllid proteins with high confidence. Oviposition and nymphal development were also evaluated across citrus hosts, revealing higher numbers of nymphs developing on lemon than on SwO. Feeding on SwO enriched pathways related to “transmission across chemical synapses” and “metabolism of proteins”. Responses observed under a 24-hour sucrose-only diet enriched the biological processes “response to external stimulus”, “response to stress” and “cytoskeleton organization”. In contrast, these enrichments were absent on lemon host, suggesting that lemon provides a more favourable environment for psyllid development. In addition, nymphs developed on lemon exhibited enhanced energy metabolism and an increase in translation initiation factors. Overall, the results demonstrate that development strongly depends on host plant species, with SwO impairing optimal growth and lemon promoting successful nymphal development.
From prediction to precision: leveraging LLMs for equitable and data-driven writing placement in developmental education
Publication . Da Corte, Miguel; Baptista, Jorge
Accurate text classification and placement remain challenges in U.S. higher education, with traditional automated systems like Accuplacer functioning as “black-box” models with limited assessment transparency. This study evaluates Large Language Models (LLMs) as complementary placement tools by comparing their classification performance against a human-rated gold standard and Accuplacer. A 450-essay corpus was classified using Claude, Gemini, GPT-3.5-turbo, and GPT-4o across four prompting strategies: Zero-shot, Few-shot, Enhanced, and Enhanced+ (definitions with examples). Two classification approaches were tested: (i) a 1-step, 3 class classification task, distinguishing DevEd Level 1, DevEd Level 2, and College-level texts in one single run; and (ii) a 2-step classification task, first separating College vs. Non-College texts before further classifying Non-College texts into DevEd sublevels. The results show that structured prompt refinement improves the precision of LLMs’ classification, with Claude Enhanced + achieving 62.22% precision (1 step) and Gemini Enhanced + reaching 69.33% (2 step), both surpassing Accuplacer (58.22%). Gemini and Claude also demonstrated strong correlation with human ratings, with Claude achieving the highest Pearson scores (ρ = 0.75; 1-step, ρ = 0.73; 2-step) vs. Accuplacer (ρ = 0.67). While LLMs show promise for DevEd placement, their precision remains a work in progress, highlighting the need for further refinement and safeguards to ensure ethical and equitable placement.