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- Emerging Trends in Higher Education: Technological Progress, Shifts in Student Populations, and Changing Workforce NeedsPublication . Peixoto, Cristina; Cecília Agostinho; Fialho, Joana; Márcio Nascimento; Antunes, Maria JoséThe higher education sector is undergoing significant changes driven by technological advancements, changing student demographics, and evolving workforce demands. Emerging trends shaping the future of higher education include personalized learning powered by adaptive technologies and artificial intelligence, the rise of short-term skill-specific certifications, virtual and augmented reality enhancing learning experiences, data- driven decision-making, interdisciplinary programs fostering critical thinking, global collaboration through online platforms, competency-based education prioritizing mastery, artificial intelligence and machine learning. This will enable personalized learning, lifelong learning initiatives supporting continuous education, increased focus on mental health and well- being, and alternative funding models like income share agreements and corporate partnerships. While these trends offer promising opportunities, they also present challenges related to equity, privacy, and balancing market demands with academic integrity. The aim of this study is to explore each of these trends, understand their implications, and evaluate the impact of the transformations they bring to the future of higher education.
- SSENPV's Integrated Management PlatformPublication . Pinto, Bruno; Matos, Cristina Peixoto; Abrantes, Steven; Lourenço, Carolina; Fialho, Joana; Cravo, Ivone; Antunes, Maria José; Nascimento, MárcioAt the Polytechnic of Viseu (PV) [1], the number of students has been increasing [2], and it is hoped that this trend continues, for the sake of the literacy of the population that serves in its area of coverage and for the reduction of the desertification of the interior region in which is inserted. In the case of Students with Specific Educational Needs (SSEN) who attend the PV (SSENPV), it is extremely important to develop procedures that minimize the anxiety brought about by change for these students, as well as to facilitate their adaptation, to make the period of permanence in Higher Education (HE) an inclusive period, generating well-being, promoting academic success, and facilitating the transition to active life. To combat this phenomenon and since the PV is a Higher Education Institution (HEI) that is guided by equity in its community, in particular the student community, the SSENPV census is a crucial measure insofar as it is necessary to implement procedures, which must respect and obey individual specificities. It is also intended that, regarding access to information on the platform, it will allow reducing asymmetries between students as well as access to services. To respond to this reality, within the scope of the Inova & Includes project. IPV I2 [3], a group of researchers, in partnership with the degree course in Computer Engineering at the Superior School of Technology and Management of Viseu (ESTGV) – curricular unit of “Project”, developed an integrated management platform for SSENPV. This platform, which is intended to be a contribution to true equity in education in the PV, is based on the support of social impact in different dimensions, which translates into the implementation of the following profiles: • Informative Profile: dissemination of legislation and other relevant information on Specific Educational Needs (SEN), ensuring centralized and accessible information management and streamlining procedures and support measures. • Academic Profile: registration and updating of data on the SSENPV. • Technical Evaluation and Follow-up Profile: registration of the SSENPV procedural evaluation, with automatic sending of technical evaluations to authorized users
- Center of Portugal Tourism: Effects of Video Advertisements on Positive Emotions and Narrative TransportationPublication . Santos, Sara; Vasconcelos, Maria; Ferreira, Sónia; Augusto, Luísa; Santo, Pedro EspíritoNowadays, it is possible to acknowledge the appeal of online platforms for advertising or the growing popularity of videos as a form of viewer engagement and entertainment. In video advertising, the narrative framework significantly impacts how the message is interpreted, particularly when storytelling techniques are applied. Moreover, the quality and format of the advertising's message directly impact consumers' intention to make a purchase. Recently, short movies have become very popular and offer much promise for marketing travel. The way that the advertisement presents the location can have a significant impact on how people feel towards the destination. Through the creation of compelling advertisements, marketers can significantly impact customer feelings, piquing their interest in destinations. A total of 906 responses were gathered for the study, and the data were analyzed using structural equation modelling and the SMART-PLS program. All the hypotheses that were tested were confirmed, indicating that the narrative structure, transportation, and advertisement design all had a significant impact on the development of positive feelings in the viewers of the promotional videos. Therefore, the narrative and design of the advertising influence the positive emotions of tourists who see this ad. These findings bolster the body of knowledge regarding using narratives in travel videos and imply that promotional videos can effectively accomplish destination marketing. Moreover, these carry repercussionsfor marketing professionals, giving them invaluable guidance on producing compelling and memorable content for travel-related videos.
- SLE-DAS enables an accurate definition of severe lupus disease activity: derivation and validation in a post hoc study of anifrolumab phase II and III studiesPublication . Diogo Jesus; Matos, Ana; Henriques, Carla; Andrea Doria; Luis Sousa InesObjectives This study aimed to derive and validate a cutoff for severe disease activity (SDA) using the SLE Disease Activity Score (SLE-DAS) and compare its accuracy and impact on health-related quality of life (HR-QoL) with the British Isles Lupus Assessment Group 2004 (BILAG-2004) and SLE Disease Activity Index 2000 (SLEDAI-2K). Methods We performed a post hoc analysis of pooled placebo arm data from the MUSE (A Phase II, Randomized Study to Evaluate the Efficacy and Safety of MEDI-546 in Subjects with Systemic Lupus Erythematosus), TULIP-1 and TULIP-2 (Treatment of Uncontrolled Lupus via the Interferon Pathway) trials, including 438 patients with moderate-to-severe SLE. SLE-DAS was scored retrospectively, and a cut-off for SDA was derived using receiver operating characteristic (ROC) curves against the BILAG-2004 numerical score >11 as gold standard. Multiple linear regression analysis and Cohen’s d effect size were applied to evaluate the effectiveness of SLEDAS, BILAG-2004 and SLEDAI-2K SDA classifications in capturing HR-QoL patient-reported outcomes (PROs). Results The optimal SLE-DAS cut-off for SDA was >9.90 (area under the ROC curve=0.847, sensitivity=77.8%, specificity=79.6%). Patients classified as SDA by both SLE-DAS and BILAG-2004 or only by SLE-DAS exhibited similar disease activity, while those classified by BILAG-2004 alone had less severe disease and better HR-QoL. The SLE-DAS cut-off was associated with worse HR-QoL across multiple PROs more consistently than BILAG-2004 or SLEDAI-2K. Conclusion The SLE-DAS cut-off for SDA provides an accurate definition of SDA in SLE, with good discriminative power and consistent associations with worse HR-QoL. This SLE-DAS definition enhances disease activity classification and offers a practical tool for guiding treatment decisions in clinical practice, as well as selecting patients with SDA for inclusion in clinical trials.
- SLE-DAS remission and low disease activity states discriminate drug from placebo and better health-related quality of lifePublication . Jesus, Diogo; Henriques, Carla; Matos, Ana; Doria, Andrea; Inês, Luís S.Objective. Our objective was to evaluate the ability of Systemic Lupus Erythematosus Disease Activity Score (SLE-DAS) remission and low disease activity (LDA) to discriminate active drug from placebo and to discriminate outcomes in the patients’ perspective (health-related quality of life [HR-QoL]) in SLE trials. Methods. This was a post hoc analysis of the pooled Belimumab in Subjects With SLE (BLISS)-52 (NCT00424476) and BLISS-76 (NCT00410384) trials data. SLE-DAS remission and LDA attainment and discrimination between belimumab and placebo at 52 weeks were compared using chi-square tests. At week 52, 36-item Short Form Health Survey (SF-36) and Functional Assessment of Chronic Illness Therapy Fatigue (FACIT-F) scores were compared between patients attaining SLE-DAS remission versus nonremission and SLE-DAS LDA versus non-LDA using the ttest and Mann-Whitney test. Mean changes from week 0 to 52 in SF-36 and FACIT-F scores were compared between groups using multivariate regression analysis adjusted for baseline scores. Results. At week 52, significantly more patients attained SLE-DAS LDA taking belimumab 1 mg/kg (17.9% vs 13.0%; P = 0.023; odds ratio [OR] 1.459; relative risk [RR] 1.377; number needed to treat [NNT] 20.4) and 10 mg/kg (21.7% vs 13.0%; P < 0.001; OR 1.853; RR 1.668; NNT 11.5) compared with placebo. Likewise, more patients attained SLE-DAS remission taking belimumab 10 mg/kg compared to placebo (14.7% vs 10.1%; P = 0.019; OR 1.532; RR 1.454; NNT 21.7). At week 52, patients attaining SLE-DAS remission and LDA presented higher SF-36 domain and summary scores (all P < 0.001) and FACIT-F scores (both P < 0.001). Mean improvements from baseline in SF-36 and FACIT-F scores were significantly higher in patients achieving SLE-DAS remission and LDA. Conclusion. SLE-DAS remission and LDA showed discriminant ability for identifying patients receiving active drug in SLE clinical trials. Attainment of these SLE-DAS targets are associated with better HR-QoL.
- The relationship between acute pain and other types of suffering in pre-hospital trauma victims: An observational studyPublication . Mota, Mauro; Melo, Filipe; Henriques, Carla; Matos, Ana; Castelo-Branco, Miguel; Monteiro, Mariana; Reis Santos, Margarida; Madalena Jesus Cunha Nunes, MariaBackground: Acute pain is an important complaint reported by trauma victims, however, the relationship between it and other types of discomfort, such as discomfort caused by cold, discomfort caused by immobilization, and psychological distress such as fear, anxiety, and sadness is limitedly studied and documented. Aim: To assess the relationship between acute trauma pain and other types of suffering in pre-hospital trauma victims. Methods: This is a prospective multicentre cohort study conducted in Immediate Life Support Ambulances in Portugal. All adult trauma victims with a mechanism of blunt and penetrating injuries, falls, road accidents and explosions, were included. Results: 605 trauma victims were included, mainly male, with a mean age of 53.4 years. Before the intervention of the rescue teams, 90.5 % of the victims reported some level of pain, 39.0 % reported discomfort caused by cold, while 15.7 % felt fear, 8.4 % sadness, 49.8 % anxiety and 4.5 % apathy. Victims with high discomfort caused by cold tend to have higher pain levels. Significantly higher pain intensity were observed in victims with fear and anxiety. Univariate and multivariate analysis indicates that immobilization is associated with increased pain levels. Conclusions: There is a statistically significant relationship between acute trauma pain, anxiety, fear, cold and immobilization.
- The Paradox Between Concept Knowledge and Digital Maturity Level for Industry 4.0: The Portuguese CasePublication . Guimarães, André; Rosivalda Pereira; Maria Teresa Pereira; Afonso Carvalho; Reis, Pedro; Antonio J. Marques Marques CardosoThis study examines whether companies’ knowledge of the Industry 4.0 concept, geographic location, and size influence the digital maturity of Portuguese industrial firms. Data were collected through a self-assessment questionnaire based on the IMPULS model and analyzed using ordinal logistic regression and chi-square tests to test three hypotheses. The results show that none of these factors significantly affects digital maturity, suggesting that isolated variables do not fully explain digital progress and that broader contextual elements, such as support programs and internal digital strategies, may play a more decisive role. The study meets its objectives and contributes to understanding digital readiness in the Portuguese industrial context. Future research should incorporate additional variables, employ longitudinal or sector-specific approaches, and utilize qualitative methods to enhance the analysis further.
- Performance Comparison of Python-Based Complex Event Processing Engines for IoT Intrusion Detection: Faust Versus StreamzPublication . Abbasi, Maryam; Cardoso, Filipe; ANTUNES VAZ, PAULO JOAQUIM; Silva, José; Sá, Filipe; Martins, PedroThe proliferation of Internet of Things (IoT) devices has intensified the need for efficient real-time anomaly and intrusion detection, making the selection of an appropriate Complex Event Processing (CEP) engine a critical architectural decision for security-aware data pipelines. Python-based CEP frameworks offer compelling advantages through the seamless integration with data science and machine learning ecosystems; however, rigorous comparative evaluations of such frameworks under realistic IoT security workloads remain absent from the literature. This study presents the first systematic comparative evaluation of Faust and Streamz—two Python-native CEP engines representing fundamentally different architectural philosophies—specifically in the context of IoT network intrusion detection. Faust was selected for its actor-based stateful processing model with native Kafka integration and distributed table support, while Streamz was selected for its reactive, lightweight pipeline design targeting high-throughput stateless processing, making them representative of the two dominant paradigms in Python stream processing. Although both engines target different application niches, their performance characteristics under realistic CEP workloads have never been rigorously compared, leaving practitioners without empirical guidance. The primary evaluation employs an IoT network intrusion dataset comprising 583,485 events from 83 heterogeneous devices. To assess whether the observed performance characteristics are specific to this single dataset or generalize across different workload profiles, a secondary IoT-adjacent benchmark is included: the PaySim financial transaction dataset (6.4 million records), selected because its event schema, fraud-pattern temporal structure, and volume differ substantially from the intrusion dataset, providing a stress test for cross-workload robustness rather than a claim of domain equivalence. We acknowledge the reviewer’s valid point that a second IoT-specific intrusion dataset (such as TON_IoT or Bot-IoT) would constitute a more directly comparable validation; this is identified as a priority for future work. The load levels used in scalability experiments (up to 5000 events per second) intentionally exceed the dataset’s natural rate to stress-test each engine’s architectural ceiling and identify saturation thresholds relevant to large-scale or multi-sensor IoT deployments. We conducted controlled experiments with comprehensive statistical analysis. Our results demonstrate that Streamz achieves superior throughput at 4450 events per second with 89% efficiency and minimal resource consumption (40 MB memory, 12 ms median latency), while Faust provides robust intrusion pattern detection with 93–98% accuracy and stable, predictable resource utilization (1.4% CPU standard deviation). A multi-framework comparison including Apache Kafka Streams and offline scikit-learn baselines confirms that Faust achieves detection quality competitive with JVM-based alternatives (Faust: 96.2%; Kafka Streams: 96.8%; absolute difference of 0.6 percentage points, not statistically significant at p = 0.318) while retaining the Python ecosystem advantages. Statistical analysis confirms significant performance differences across all metrics (p < 0.001, Cohen’s d > 0.8). Critical scalability thresholds are identified: Streamz maintains efficiency above 95% up to 3500 events per second, while Faust degrades beyond 2500 events per second. These findings provide IoT security engineers and system architects with actionable, empirically grounded guidance for CEP engine selection, establish reproducible benchmarking methodology applicable to futurePython-based stream processing evaluations, and advance theoretical understanding of the accuracy–throughput trade-off in stateful versus stateless Python CEP architectures.
- Menus as Instruments for Communicating Endogenous Products The case of Restaurants in Pousadas de PortugalPublication . Barroco, Cristina; Gonçalves, TiagoRestaurant menus can be much more than the presentation of dishes, they can showcase a set of endogenous products, while at the same time allowing the customer to get to know a little more about the territory, through gastronomy. When done well, menus can be instruments for promoting gastronomic tourism, taking customers on authentic journeys through the flavours and knowledge of the territory. The main aim of this paper is to identify how endogenous products are being communicated in menus, using the case study of Pousadas de Portugal restaurants for this purpose. The menus of three restaurants were analysed using a grid that made it possible to identify which endogenous products were presented and how this information was transmitted to the customer. The analysis allowed us to conclude that all the restaurants offer contemporary regional cuisine representative of the territories in which they are located. All menus feature short, interesting stories about some of the dishes. The word "Regional" appears several times on the menus and the dishes' names mention some territories. To complement the analysis, 25 chefs were surveyed, who were asked about the importance of including local products in their menus. Promoting these products can help preserve and showcase the unique cultural identity of a region and can contribute to sustainable development and environmental conservation.
- Unified Data Governance in Heterogeneous Database Environments: An API-Driven Architecture for Multi-Platform Policy EnforcementPublication . Abbasi, Maryam; ANTUNES VAZ, PAULO JOAQUIM; Silva, José; Cardoso, Filipe; Sá, Filipe; Martins, Pedro; Cardoso, Filipe; Sá, Filipe; Martins, PedroModern organizations increasingly rely on heterogeneous database environments that combine relational, document-oriented, and key-value storage systems to optimize performance for diverse application requirements. However, this technological diversity creates significant challenges for implementing consistent data governance policies, regulatory compliance, and access control across disparate systems. Traditional governance approaches that operate within individual database silos fail to provide unified policy enforcement and create compliance gaps that expose organizations to regulatory and operational risks. This paper presents a novel API-driven architecture that enables unified data governance across heterogeneous database environments without requiring database-specific modifications or vendor lock-in. The proposed framework implements a centralized governance layer that coordinates policy enforcement across PostgreSQL, MongoDB, and Amazon DynamoDB systems through RESTful API interfaces. Key architectural components include differentiated access control through hierarchical API key management, automated compliance workflows for regulatory requirements such as GDPR, real-time audit trail generation, and comprehensive data quality monitoring with automated improvement mechanisms. Comprehensive experimental evaluation demonstrates the framework’s effectiveness across multiple operational dimensions. The system achieved 95.2% accuracy in access control enforcement across different data classification levels, while automated GDPR compliance workflows demonstrated 98.6% success rates with average processing times of 2.9 h. Performance evaluation reveals acceptable overhead characteristics with linear scaling patterns for PostgreSQL operations (R2 = 0.89), consistent sub-20ms response times for MongoDB logging operations, and sustained throughput rates ranging from 38.9 to 142.7 requests per second across the integrated system. Data quality improvements ranged from 16.1% to 34.3% across accuracy, completeness, consistency, and timeliness dimensions over a 12-week monitoring period, with accuracy improving by 17.8 percentage points, completeness by 13.2 percentage points, consistency by 19.7 percentage points, and timeliness by 24.5 percentage points. The duplicate detection system achieved 94.6% precision and 95.6% recall across various duplicate types, including cross-database redundancy identification. The results demonstrate that API-driven governance architectures can effectively address the persistent challenges of policy fragmentation in multi-database environments while maintaining operational performance and enabling measurable improvements in data quality and regulatory compliance. The framework provides a practical migration path for organizations seeking to implement comprehensive governance capabilities without replacing existing database infrastructure investments.