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- Relationship between social support and psychological symptoms in people living with HIV/AIDS, at risk of developing HIV – associated dementiaPublication . Sousa, Gilberta; Padilha, José Miguel dos Santos Castro; Costa, Patrício; Abreu, Wilson Jorge Correia; Sousa, GilbertaABSTRACT People living with HIV/AIDS often present neuropsychiatric symptoms, including cognitive and mood-related manifestations. Social support helps to cope with adverse events related to mental health. We aimed to analyze the relationship between satisfaction with social support and psychological symptoms in people living with HIV/AIDS at risk of developing HIV-associated dementia. An observational, cross-sectional, and correlational study was conducted. Assessment instruments included: sociodemographic questionnaire; Social Support Scale for People Living with HIV [Seidl & Tróccoli, 2006. Development of a scale for the social support evaluation in HIV/AIDS. Psicologia: Teoria e Pesquisa, 22(3), 317–326.], Brief Symptom Inventory (BSI) [Canavarro, 1999. Psychopathological Symptom Inventory – BSI. In M. G. M. R. Simões, & L. S. Almeida (Eds.), Psychological tests and tests in Portugal (Vol. II, pp. 87–109). SHO/APPORT.]; and International HIV Dementia Scale (IHDS). The sample consisted of 255 participants with a mean age of 48.16 years, 80.8% male, 68.6% living mostly with someone else. The strongest correlation was between the perception of availability of emotional support and availability of instrumental support, r (255) = 0.992; p < 0.001. Individuals with higher satisfaction with perceived emotional support had fewer psychological symptoms. Those with a higher Global Severity Index score on the BSI had a higher risk of dementia. An association was found between symptoms of psychological distress and a higher likelihood of developing HIV-related dementia. To reduce the risk of HIV-associated dementia, it is imperative to improve social support networks, which can serve as a vital clinical strategy.
- Assessing essential oils from Macaronesia: a study on their efficacy against phytopathogenic and obligate biotrophic fungiPublication . Ferreira, Rui Miguel; Pereira, Verónica Sousa; Sardinha, Duarte Fernandes; Rodríguez Sabina, Samuel; Cabrera Pérez, Raimundo; Castilho, Paula Machado; Castilho, Paula CBACKGROUND: Essential oils (EOs) extracted from eight culinary herbs and spices, some endemic to Macaronesia flora (Cedro nella canariensis, Clinopodium ascendens and Laurus novocanariensis) and others common in Mediterranean cuisine (Cinnamo mum burmannii, Ocimum gratissimum, Origanum vulgare subsp. virens, Syzygium aromaticum and Thymus vulgaris) were evaluated via direct-contact bioassays, both in vitro and in vivo, against three species of phytopathogenic fungi (Alternaria alternata, Botrytis cinerea, and Fusarium oxysporum) and the obligatory biotrophic fungus Oidium farinosum. Carvacrol-rich Origanum vulgare was selected to study the influence of isomerism on bioactivity, because Thymus vulgaris is rich in thymol, a structural isomer of carvacrol. RESULTS:FiveEOsexhibitedstrongtomoderateantifungalactivityandwerefurtherscreenedatlowerconcentrationstoassess their toxicity and growth inhibition thresholds. Cedronella canariensis showed no antifungal activity, whereas Laurus novoca nariensis demonstrated only weak activity against Botrytis cinerea. This fungus was more susceptible to the tested EO than the other phytopathogenic fungi. Origanum vulgare was slightly more effective than Thymus vulgaris, for all three phytopath ogenic fungi. Ocimum gratissimum, Syzygium aromaticum, and Cinnamomum burmannii significantly reduced powdery mildew severity, whereas Origanum vulgare and Thymus vulgaris showed moderate activity. CONCLUSION:Phenylpropanoid-rich EOs, such as Cinnamomum burmannii, Ocimum gratissimum, and S. aromaticum, exhibited the strongest antifungal activity in both bioassays with phytopathogenic and obligate biotrophicfungi.Ourresults confirmthe higher antifungal activity of the phenylpropanoid class of EOs.
- Emotional competencies and physical activity in primary school children: a comparative study across levels of learning supportPublication . Antunes, Filipa; Antunes, Hélio; Rodrigues, Ana; Sabino, Bebiana; Ashraf, Sadaf; Sousa, Duarte; Carvalho, Joana; Antunes, Hélio; Rodrigues, Ana; Sousa, DuarteChildren’s emotional development is a determining factor for their school success and overall well-being. Additionally, physical activity is recognized as a relevant contribution in promoting emotional self-regulation, self-esteem, and social inclusion. This aspect is especially important in the inclusive educational context, where it seeks to respond to the needs of students with learning difficulties through diversified support measures. The study aimed to analyse the relationship between differentiation and emotional identification indices and levels of physical activity in primary school children (ages 6–10). Three distinct groups were considered: students without Learning and Inclusion Support Measures (No-LISM), with Selective Learning and Inclusion Support Measures (S-LISM), and with Universal Learning and Inclusion Support Measures (U- LISM). The sample size consisted of 69 children (mean age = 814 ± 1.13 years). Data were collected on sports practice and physical activity using accelerometry, as well as emotional indices were collected through the Inventory of Identification of Emotions and Feelings. The results revealed statistically significant differences in emotional indices between the groups, with No-LISM students presenting higher levels of differentiation and emotional identification. In contrast, students with U-LISM demonstrated higher levels of moderate to vigorous physical ac tivity. It is concluded that, although physical activity is important in the inclusive educational context, its associations on emotional development are not always consistent. These results suggest the need for more structured psychoeducational strategies to enhance the potential impact of physical activity on emotional development, particularly in students with greater support needs.
- Short-term market impact of 2024 US President elections and Trump-Zelensky meeting in defence industryPublication . Martins, António Miguel; Albuquerque, Bruno; Sardinha, Luís; Moutinho, Nuno; Martins, António; Albuquerque, Bruno; Sardinha, LuisThis study examines the short-term market effect of the US and European largest defence firms on the 2024 US presidential election (November 5, 2024) and the Trump-Zelensky meeting (February 28, 2025). By employing an event study methodology, our results show a positive and statistically significant stock price impact for both events. The results for the 2024 US presidential election are consistent with political business cycle theory. National elections in the arms- producing country drive a growth in sales revenues for defence firms, which tend to be higher when the Republican Party candidate wins the US elections. Our results also show the presence of heterogeneous abnormal returns between US and European defence firms around the Trump- Zelensky meeting, with European firms showing high and statistically significant positive returns while US firms show non-significant returns. This result is explained by the failure of security guarantees given by the US to the European countries and the awareness of the need for a rapid increase in military spending for self-defence purposes in Europe. This meeting reinforced the application of the principle of “Europe preference” in the acquisition of weapons. Finally, we conclude that stock market responses are reinforced or mitigated by firm-specific characteristics.
- Development and preliminary validation of an analytical methodology for the determination of organic UV filters in zooplankton samplesPublication . Íñiguez, Eva; Gouazé, Margaux; Dinis, Ana; Sosa-Ferrera, Zoraida; Cordeiro, Nereida; Kaufmann, Manfred; Montesdeoca-Esponda, Sarah; Iñiguez Santamaría, Eva; Dinis, Ana; cordeiro, nereida; Kaufmann, ManfredThe release of chemicals into marine environments from coastal human activities has raised growing concern about pollution. Among these chemicals, organic ultraviolet filters (oUVFs), widely used in personal care products and industrial applications, have recently been identified as pollutants of emerging concern. Their extensive use and persistence highlight the need to assess their occurrence and potential impacts on aquatic ecosystems. This study aimed to optimize and apply an analytical methodology for the determination of eleven oUVFs in zooplankton matrices. Microwave-assisted extraction (MAE) was employed for sample preparation, while ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) enabled the identification and quantification of the target compounds. Extraction parameters, including solvent, temperature, and time, were systematically optimized to enhance recovery and ensure accuracy and precision in complex biological samples. The method achieved limits of detection (MLOD) between 1.47 and 5.98 ng g weight (d.w.) and method limits of quantification (MLOQ) between 4.900 and 19.92 ng g 1 1 dry d.w. Recovery ef ficiencies were low, ranging from 28 to 63 %, reflecting the diverse physicochemical properties of oUVFs and the strong matrix effects associated with zooplankton heterogeneity. Application of the validated method to zooplankton collected around Madeira Island (Portugal) revealed the presence of six oUVFs. Homosalate was the most frequently detected compound (53 % of samples), while octocrylene exhibited the highest concentrations, ranging from 24.01 to 1029 ng g 1 d.w. These findings demonstrate the relevance of zooplankton as bio indicators of oUVF contamination and support the need for regulatory monitoring and ecological risk assess ments in coastal ecosystems.
- User profiling and its dynamics: a narrative reviewPublication . Freitas, Diogo Nuno; Varela, Katherin; Fermé, Eduardo; Freitas, Diogo Nuno; Varela, Katherin; Fermé, EduardoThe need for personalized content has grown considerably with the increasing amount of online information. User profiles, as structured collections of user characteristics and interests, are essential for personalization because they help systems better understand individual preferences and deliver more relevant content. This review examines methods for user profiling and their adaptation over time. We organize existing literature into five categories: User Profile Modeling, Profile Dynamics, Recommendation Systems, Personalized Systems, and Adaptive Systems. Key findings highlight the importance of combining explicit and implicit data collection methods, differentiating between short- and long-term user preferences, and employing techniques such as evolutionary algorithms, context-awareness, and explainability. Additionally, we identify promising areas for future research, including multimodal data integration, scalability, privacy preservation, contextual adaptation, and universal user models. This review aims to help readers navigate the extensive literature and provide insights to support the development of practical applications based on user profiling techniques.
- Stock market effects of CrowdStrike IT outage on largest listed hotel companiesPublication . Albuquerque, Bruno; Cró, Susana; Moutinho, Nuno; Martins, António Miguel; Albuquerque, Bruno; Martins, AntónioThis study analyses the short-term market effect of CrowdStrike IT outage in the 100 largest worldwide listed hotel companies. Using an event study methodology, the paper analyses how hotel companies are penalized by the market to the biggest IT disruption in history. Our results evidence a statistically significant negative reaction around the event date. This result is explained by the adverse impact caused by IT failures in the hotel’s business operations (reservation, payment, technical systems) and supply chain processes, which result in financial losses. We also observe a highest negative stock market reaction for hotel companies located in Western countries and for hotels with a low cyber risk rating. Finally, this study identifies hotel-specific characteristics that drive value during an IT outage. The research evidence that larger and more profitable hotel companies, with lower leverage and higher cyber risk ratings are more resilient to the adverse effects of IT outages.
- Bioinspired hybrid DNA/dendrimer-based films with supramolecular chiralityPublication . Castro, Rita; Granja, Pedro L.; Rodrigues, João; Pêgo, Ana Paula; Tomás, Helena; Castro, Rita; Rodrigues, João; Pêgo, Ana Paula; Tomás, HelenaBioinspired hybrid DNA/dendrimer films were obtained by heating long double-stranded DNA (dsDNA) above its melting temperature and, while in the denatured state, mixing it with poly(amidoamine) (PAMAM) dendrimers, followed by controlled cooling. The formation of these new types of films was found to be dependent on several parameters, including the initial heating temperature, pH, buffer composition, dendrimer generation, amine/phosphate (N/P) ratio, and cooling speed. In addition to the PAMAM dendrimers (generations 3, 4, and 5), films could also be produced with branched poly(ethylenimine) with a molecular weight of 25 kDa. The results indicated that these films were formed not only through electrostatic interactions established between the negatively charged DNA molecules and the positive dendrimers, as expected, but also through random rehybridization of the single-stranded DNA (ssDNA) during the cooling process. The resulting films are water-insoluble, transparent when thin, highly elastic when air-dried, exceptionally stable over extended periods, cytocompatible, and easily scalable. Notably, the slow cooling process allowed for the establishment of at least a partially ordered structure in the films, as revealed by circular dichroism, providing evidence of supramolecular chirality. It is envisioned that these films may have significant potential in biomedical applications, such as drug/gene delivery systems, platforms for cell-free DNA transcription and components in biosensors.
- Numerical investigation of stability of low-current needle-to-plane negative corona discharges in airPublication . Ferreira, N. G. C.; Almeida, P. G. C.; Taher, A. Eivazpour; Naidis, G. V.; Benilov, M. S .; Ferreira, Nuno; Almeida, Pedro G C; Benilov, Mikhail; Benilov, MikhailAbstract Negative DC corona discharges are known for their self-pulsing regime: the Trichel pulses. In some works, pulsed regimes, stochastic or periodic, have been observed immediately upon the inception of the discharge, while in other works the discharge was found to be ignited in a steady-state (pulseless) mode, with the Trichel pulses developing at higher voltages. Recent theoretical and modeling work showed that the stationary negative corona between concentric cylinders in atmospheric-pressure air is stable immediately after the ignition. The pulseless mode was found also in the modeling of the needle-to-plane geometry, however in a quite narrow voltage range. This work studies conditions for a pulseless negative corona discharge in a needle-to-plane geometry to occur over a wide range of voltages, which will facilitate its unambiguous observation in the experiment. After the negative corona loses stability, the current evolution shows, after a small region of quasi-harmonic oscillations, pulses. These can be of small amplitude or regular Trichel pulses, which develop via standing-wave or ionization-wave mechanisms. Modeling results agree with available experimental data, both for the current–voltage characteristics and the stability limit of the pulseless negative corona discharge. An insight is given into stochastic Trichel pulses, which have been observed in experiments under certain conditions.
- Intelligent visibility forecasting at airports: a systematic reviewPublication . Alves, Décio; Belo-Pereira, Margarida; Mendonça, Fábio; Morgado-Dias, Fernando; Alves, Decio; Silva Mendonça, Fábio Rúben; Morgado-Dias, FernandoAbstract Low visibility conditions caused by phenomena such as fog, heavy rain, or snowfall impose major operational and safety challenges at airports. Conventional numerical weather prediction models, although improved over time, still struggle to forecast low visibility accurately due to scale mismatches and uncertainties in physical parameterizations, among other factors. This review synthesizes findings on data-driven solutions, including machine learning and deep learning, that harness large datasets to reveal hidden patterns, offering better performance and adaptability. Ensemble methods and the integration of multiple data sources further enhance accuracy, particularly for short lead times. Several methods achieve correlation coefficients above 0.90 and root mean square error below 1 km, yet generalization and integration into real-time airport operations remain underexplored. Future work should focus on transferability across diverse climates, integration with advanced operational tools, and bridging gaps between model complexity and user interpretability. The next generation of hybrid forecasting frameworks has the potential to enhance safety, limit economic losses, and improve resilience in airport operations.