Abstract

Abstract
Dropout from Higher Education (HE), that is, the number of students that totally leave a given HE institution is concerningly high, especially in times of crisis. Institutions struggle to minimize dropout, but limited data is available likely because gathering data from learners who dropped out is sensitive, likely involving private information. This paper presents a case study research on student dropout from a very large Portuguese engineering faculty. The main objectives of this research include to gain a better understanding about the reasons for dropout, from the former student’s point of view, and to build a profile for the dropout-at-risk student. The collected data was retrieved from institutional records and from 134 telephonic interviews with former students. The resulting data is analysed in both quantitative and qualitative ways. Results of all gathered dropout data are clustered into three profiles of students who dropout: those that “pull out”, those who were “pushed out” and those who “fall out”. Findings include that students do not decide to dropout by a simple single reason but rather a set of reasons. This research article includes 5 concrete improvement suggestions that are likely to reduce dropout. The two main suggestions are to better prepare the transition to HE and to make policies more flexible in times of crisis, example more flexible schedule. © 2024, Author. All rights reserved.

Abstract
The satellite monitoring of vegetation moisture content (VMC) and soil moisture content (SMC) in Southern European Atlantic mountains remains poorly understood but is a fundamental tool to better manage landscape moisture dynamics under climate change. In the Atlantic humid mountains of Portugal, we investigated an empirical model incorporating satellite (Sentinel-1 radar, S1; Sentinel-2 optical, S2) and ancillary predictors (topography and vegetation cover type) to monitor VMC (%) and SMC (%). Predictors derived from the S1 (VV, HH and VV/HH) and S2 (NDVI and NDMI) are compared to field measurements of VMC (n = 48) and SMC (n = 48) obtained during the early, mid and end of summer. Linear regression modelling was applied to uncover the feasibility of a landscape model for VMC and SMC, the role of vegetation type models (i.e. native forest, grasslands and shrubland) to enhance predictive capacity and the seasonal variation in the relationships between satellite predictors and VMC and SMC. Results revealed a significant but weak relationship between VMC and predictors at landscape level (R2 = 0.30, RMSEcv = 69.9 %) with S2_NDMI and vegetation cover type being the only significant predictors. The relationship improves in vegetation type models for grasslands (R2 = 0.35, RMSEcv = 95.0 % with S2_NDVI) and shrublands conditions (R2 = 0.52, RMSEcv = 45.3 %). A model incorporating S2_NDVI and S1_VV explained 52 % of the variation in VMC in shrublands. The relationship between SMC and satellite predictors at the landscape level was also weak, with only the S2_NDMI and vegetation cover type exhibiting a significant relationship (R2 = 0.28, RMSEcv = 18.9 %). Vegetation type models found significant associations with SMC only in shrublands (R2 = 0.31, RMSEcv = 9.03 %) based on the S2_NDMI and S1_VV/VH ratio. The seasonal analysis revealed however that predictors associated to VMC and SMC may vary over the summer. The relationships with VMC were stronger in the early summer (R2 = 0.31, RMSEcv = 90.1 %; based on S2_NDMI) and mid (R2 = 0.37, RMSEcv = 70.8 %; based on S2_NDVI), butnon-significant in the end of summer. Similar pattern was found for SMC, where the link with predictors decreases from the early summer (R2 = 0.33, RMSEcv = 16.0 %; based on S1_VH) and mid summer (R2 = 0.30, RMSEcv = 17.8 %; based on S2_NDMI) to the end of summer (non-significant). Overall, the hypothesis of a universal landscape model for VMC and SMC was not fully supported. Vegetation type models showed promise, particularly for VMC in shrubland conditions. Sentinel optical and radar data were the most significant predictors in all models, despite the inclusion of ancillary predictors. S2_NDVI, S2_NDMI, S1_VV and S1_VV/VH ratio were the most relevant predictors for VMC and, to a lesser extent, SMC. Future research should quantify misregistration effects using plot vs. moving window values for the satellite predictors, consider meteorological control factors, and enhance sampling to overcome a main limitation of our study, small sample size.

Abstract
In the health sector, the implementation of qualitative data research is very important to improve overall services. However, the use of these methods remains relatively unexplored when compared to quantitative analyses. This article describes the qualitative data analysis process that is based on the description, analysis and interpretation of data. It also describes a practical case study and the use of NVivo software to assist in the development of a theory-based qualitative analysis process. This article intends to be a step forward in the use of qualitatively based methodologies in future research in the health sector.

Abstract
With the ubiquitous use of mobile applications, it is paramount that they are accessible, so they can empower all users, including those with different needs. Determining if an app is accessible implies conducting an accessibility evaluation. While accessibility evaluations have been thoroughly studied in the web domain, there are still many open questions when evaluating mobile applications. This paper investigates mobile accessibility evaluation methodologies. We conducted four studies, including an examination of accessibility reports from European Member-states, interviews with accessibility experts, manual evaluations, and usability tests involving users. Our investigations have uncovered significant limitations in current evaluation methods, suggesting that the absence of authoritative guidelines and standards, similar to what exists for the web, but tailored specifically to mobile devices, hampers the effectiveness of accessibility evaluation and monitoring activities. Based on our findings, we present a set of recommendations aimed at improving the evaluation methodologies for assessing mobile applications' accessibility.

Abstract
Este artículo presenta un modelo de programación lineal entera mixta para resolver el problema de selección óptima del tamaño del conductor en sistemas de distribución radial considerando la integración de comunidades energéticas locales. La operación en estado estable del sistema de distribución basado en inyecciones de corriente se modela utilizando técnicas de linealización. La formulación propuesta considera la presencia de comunidades energéticas locales y restricciones operativas tales como límites de magnitud de voltaje y corriente. La formulación presentada se probó en un sistema de distribución utilizado en la literatura especializada. Los resultados muestran la eficiencia del método y demuestran que el modelo puede ser utilizado como solución del problema de selección óptima del tamaño del conductor.