The aim of this paper is a comparative study between different thermal spas located within the countries of Portugal and Spain in order to reveal the degree of compliance with the variables that make up the SERVQUAL service model, considering the reviews registered by users on the Tripadvisor platform as the basis for the study. This study takes the texts of the reviews, decomposes them into different sentences, and subsequently associates them with each of the variables contemplated within the study model so as to obtain a more accurate association between the data source and the aforementioned study model. Results were taken from Tripadvisor reviews of Portuguese (n1 = 622) and Spanish (n2 = 529) thermal spas, and using the study model, a correlation analysis (r) combined with an unsupervised cluster study was performed to assess the relationships among various factors. The results obtained in both analyses were compared between the two countries. The findings frame the level of equilibrium that can be seen in the service model variables of the different thermal spas analysed. In this way, similarities and differences are revealed between spa users in the two countries analysed in terms of the key variables. It will be of great interest to academics interested in the study because of the methodology applied on the basis of Machine Learning on the data source of the reviews, which generates valuable information for tour operators for direct application in the design and development of tourism activities.

Jyväskylä is the largest city in the Central Finland and Finnish Lakeland region. In digital era places and destinations compete against each other in an increasingly globalized market. To successfully compete, destinations need to work on developing a strong brand identity through effective positioning. The main goal of this work is to understand how social media platforms has been used to create / promote the Jyvaskyla brand. An exploratory qualitative study was developed to accomplish our goals. Data were collected and analysed until October 2024. We analyse all the hashtags in the social media Instagram, Facebook, Tik ToK and YouTube defined by the municipality of Jyvaskyla, namely, #jyväskylä #liikuntapääkaupunki, #capitalofsport, #tapahtumakaupunki, #opiskelijakaupunki, #visitjyväskyläregion, #visitjyvaskylaregion, #valonkaupunki, #cityoflight. Based on these hashtags, the posts created by users of these platforms were analysed, namely the content of the posts they associate with the city, the author of the publication and their geographical region, and the date of publication of the posts. The data was collected using the platform Apify, and all the posts were analysed with content analysis to understand the main keywords associated with the brand Jyvaskyla. Moreover, posts were analysed using the sentiment analysis tool Benty.ai, which uses artificial intelligence to analyse the tone with which the text was written. Our preliminary results show the importance of the definition of a brand for the city as a marketing strategy. When we regard the hashtags defined by municipality, they have the name of the city or associated the term “city” to the brand they want to promote, namely: sports, events, light or study. The current study provides valuable information on the current state of social media communication from stand points of branding and destination marketing. Also gives the opportunity to access and compare the effectiveness of these four platforms. Decision-makers needs to understand how to enhance the use of this technology to promote tourism destinations.

Clinical communication skills are essential for building trust between healthcare professionals and patients. Clear and empathetic communication fosters shared decision-making, enhances therapeutic adherence, and improves outcomes. This is particularly significant for professionals such as physicians, nurses, and allied health professionals (e.g., physiotherapists), who work closely with individuals requiring personalized feedback and interaction. This systematic review followed PRISMA guidelines to expand the existing knowledge and aimed to answer the question: What is the importance of clinical communication in healthcare interventions? Academic databases (EBSCO, Scopus, Web of Science, and PubMed) were searched for peerreviewed articles published within the last decade, examining the role and components of clinical communication in healthcare interventions. Studies included diagnoses, as mental and neurocognitive conditions, and COVID-related care, while excluding those focused on physical illnesses, pharmacology, or interventions targeting only patients’ empathy/cognition. Forty-two studies were qualitatively analyzed and grouped by communication strategies, settings, populations, and key competencies. The findings underscore empathy as a core competency, consistently linked to enhanced professional effectiveness and stronger therapeutic relationships. Several studies emphasized how patient-centred communication improved satisfaction, adherence to treatment, and collaboration. Additionally, integrating emerging technologies, such as telehealth platforms and digital communication tools, was identified as a growing area of interest, bringing both new opportunities and challenges to clinical practice. Based on the findings, we recommend that communication training be embedded in healthcare curricula through simulations, reflective practice, and interdisciplinary education. Preparing future professionals in this field is crucial to ensuring quality clinical care.

A disciplina de Análise e Visualização de Dados em Saúde, integrada na Licenciatura em Saúde Digital do Politécnico do Porto, explora novas abordagens pedagógicas centradas na tecnologia. Propõe-se a utilização do SAP Analytics Cloud como plataforma de apoio ao ensino de análise de dados em saúde, permitindo aos estudantes desenvolver competências práticas em Business Intelligence, visualização interativa e previsão de tendências (p. ex., epidemiológicas). Para potenciar a imersão e a aprendizagem ativa, será integrada a utilização de óculos como os Meta Quest 3, permitindo experiências de Realidade Virtual e Realidade Aumentada. Os estudantes poderão explorar dashboards 3D, mapas de propagação (p. ex., de doenças) e cenários de planeamento hospitalar em ambientes imersivos. Esta abordagem inovadora visa fomentar o pensamento crítico, a literacia de dados e a preparação dos futuros profissionais de saúde para os desafios digitais emergentes, alinhando o ensino com as tendências internacionais de transformação tecnológica na educação superior.

Tuberculosis (TB) is one of the most devastating infectious diseases affecting humankind, having caused 1.25 million deaths in 2023. The identification of effective protective mechanisms in TB could critically contribute to the urgent need of new therapies to stop TB. It is known that genetically related Mycobacterium tuberculosis (Mtb) isolates shape the immune response and disease outcomes. Using the natural genetic diversity of Mtb as a tool to understand protection in TB, my project focuses on the slow progressing infection caused by Mtb isolates of lineage 6 (L6), in which we hypothesize that critical protective mechanisms operate. Analyses of in vitro (macrophages) and in vivo (mouse) infections were performed in susceptible C3HeB/FeJ or resistant C57BL/6 mice, to compare the immune response and outcome of infection caused by Mtb belonging to L6 or L4. Results: In vitro (macrophage) infections showed that both Mtb L6 and Mtb L4 isolates grow overtime, but Mtb L6 grows slower than Mtb L4. In vivo, we found that C57BL/6 mice infected with Mtb L6 offer a unique model of full protection. Strikingly, flow cytometry analysis revealed a faster recruitment of activated CD4+ T cells to the lungs in the Mtb L6-infected C57BL/6, which might suggest that protection may be achieved by this early T cells recruitment. Our results indicate that a slower growth of Mtb L6 in macrophages together with earlier T cell responses in the lung may underlie fully infection control. The ongoing RNA-sequencing analyses will highlight putative protective immune mechanisms operating in this model, of great interest to devise new strategies to control TB.

The agrifood industries generate tremendous amounts of waste. The valorisation of these wastes is of the utmost importance. Here, spent coffee ground (SCG) and Cistus ladanifer L. leaf (CLL) post-distillation residues were used to prepare 50:50 (v/v) hydromethanolic extracts for green zero-valent iron nanoparticle (nZVI) production. Then, the nZVIs’ size, polydispersity index (PDI) and zeta potential (ZP) were determined through dynamic light scattering (DLS). Since nZVIs are known to be heavily reactive and display a tendency to agglomerate, dispersant influence (water or methanol) and surfactant addition (Tween® 20) were studied. SCG NPs dispersed in water displayed a size of 565.6 ± 80.84 nm, with a PDI of ± 0.084, and a ZP of −19.57 ± 0.95 mV. Adding Tween®-20 resulted in much lower sizes for these NPs (14.64 ± 0.76 nm with a PDI of 0.238 ± 0.066) and an increase in ZP (−5.99 ± 1.71 mV). CLL nZVIs dispersed in water displayed similar results, with lower size and higher ZP after surfactant addition (766.43 ± 129.49 nm, 0.684 ± 0.151 PDI vs. 13.4 ± 4.26 nm, 0.31 ± 0.042 PDI, −5.51 ± 0.86 mV). Using methanol as the dispersant for nZVIs displayed far worse results, which shows that nZVIs are better dispersed in water, and the addition of Tween® 20 highly reduced agglomeration, increasing the zeta potential. These results allow for better understanding of the importance of dispersant and surfactant usage for an accurate characterization by DLS.

Integrada na UC Educação Clínica II da E2S|Porto, foi desenvolvida uma intervenção educativa sobre hereditariedade, dirigida a 86 estudantes do 1.º ao 4.º ano do Ensino Básico (5-10 anos), em 4 sessões independentes com cerca de 45 minutos. Partindo da questão “Porque somos parecidos com os nossos pais?”, a atividade utilizou uma abordagem lúdico-pedagógica para explorar conceitos genéticos. Iniciou com a identificação de características fenotípicas familiares, como a capacidade de enrolar a língua. Seguiram-se atividades práticas com coelhos brancos/pretos em cartão para explicar dominância e recetividade, complementadas por um xadrez mendeliano com “ervilhas” de esferovite. Após a introdução aos conceitos de célula, cromossomas e DNA, os alunos realizaram um “cariótipo” usando pauzinhos de gelados com diferentes padrões de bandas, tamanhos e cores. A análise dos questionários pré e pós-intervenção revelou um aumento de respostas corretas em cada ano escolar (1º ano: >60%; 2º ano: >47%; 3º ano: >45%; 4º ano: >27%), demonstrando a eficácia da metodologia. Esta abordagem (inter)ativa, associando teoria e experiência, revelou-se eficaz na promoção do conhecimento científico e no estímulo ao interesse precoce pela ciência.

Quando alguém, até aí com uma audição normal, acorda sem ouvir, pelo menos de um ouvido, parece que tudo se desmorona, com dificuldade em ouvir no local de trabalho, nas relações familiares, surge alguma frustração e degradação da qualidade de vida do individuo.

Privatization frequently boosts efficiency and productivity in businesses as private companies are generally more motivated to reduce costs, innovate, and meet market needs than state-run counterparts. The privatization of the hospitality sector pertains to the acquisition or operational control of hospitality properties, such as hotels and resorts, including additional services, shifting from government provision to private companies. This shift can have mixed effects on environmental sustainability. This paper delves into the interplay of environmental taxes, pollution control spending, and the privatization of a partially state-owned (PSO) hotel within a mixed duopoly framework. The market we analyze comprises a single partially state-owned (PSO) hotel competing against one for-profit (FP) hotel in a five-stage game: (i) the government decides how much of the PSO hotel will be privatized; (ii) a regulator, aiming to maximize social welfare, establishes the emission tax rate; (iii) the PSO hotel selects abatement pollution investments; (iv) the FP hotel then selects pollution abatement investments; and (v) subsequently, the two hotels concurrently and autonomously determine the quantity of rooms available for reservation. This game presents a model of a policy regime featuring commitment. In contrast, our analysis also considers a non-committed regime, distinguished by the fact that step (ii) occurs after decisions regarding abatement pollution investments. This study’s most significant finding is that, according to the social welfare perspective within the analyzed models, neither total privatization nor complete nationalization represents the optimal governmental strategy.

Eating and swallowing are intricate actions comprehending both voluntary and reflexive movements, engaging over thirty nerves and muscles (1). Dysphagia occurs when the normal swallowing process is compromised, increasing the risk of the swallowed material entering the larynx, and causing complications for the patient (2). Cervical auscultation (CA) is a clinical method used to evaluate the pharyngeal phase of swallowing by listening to the sounds of swallowing-related respiration. However, the reliability of CA is susceptible to the subjectivity and experience of the speech therapist (3). The application of artificial intelligence (AI) tools in healthcare has the potential to support healthcare workers with a variety of tasks. It can be used for disease prediction and diagnostics treatment, outcome prediction and prognosis evaluation (4). Contribute to the development of an AI tool to aid speech therapists in their daily evaluation of deglutition in patients, applying machine learning algorithms to process and analyse the sound recorded during cervical auscultation. Using an electronic stethoscope, audio samples were recorded from individuals with and without pathology while they swallowed different liquid quantities (5 mL and 10 mL) and consistency (moderately thick and solid). The audio is divided into three sections (5) and pre- processed to remove unnecessary noise. Data is classified using machine learning algorithms and the models will be evaluated according to precision, accuracy, sensibility, confusion matrix and ROC curve. Previous work in this field reported by Santoso et al. (6) using supervised machine learning algorithms obtained promising results in swallowing detection. In this study, our dataset is composed of 87 samples of patients, and similar results are to be expected. AI can offer an objective and quantitative analysis of swallowing sounds, potentially providing more accurate and consistent results compared to subjective assessments. Additionally, it can identify complex patterns in swallowing sounds that may be challenging for less experienced speech therapists to recognize.