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

Abstract
The main aim of this article is to investigate the effect of perceived greenwashing on consumers' purchasing behavior of eco-friendly products. Twelve research hypotheses were defined based on contributions from the literature. To test these hypotheses, a quantitative methodology was employed, collecting data through an online survey (N = 270) and using SmartPLS for analysis. The results confirm that perceived both perceived greenwashing and perceived risk have a negative influence on consumer attitudes. While their direct effects on purchase intention were found to be insignificant, both perceived greenwashing and perceived risk had a significant negative indirect effect on purchase intention through attitude. Additionally, it was confirmed that purchase behavior is positively affected by attitude and by willingness to pay more. These results contribute to addressing the limited knowledge regarding the impact of consumers' perceived greenwashing on their behavior, especially concerning different product types. Furthermore, they provide valuable insights for managers, highlighting the importance of mitigating greenwashing and risk perceptions associated with eco-friendly products due to their indirect negative impacts on purchase intention and behavior.

Abstract
Aims. We aim to investigate the origin of the HI Br gamma emission in young stars by using GRAVITY to image the innermost region of circumstellar disks, where important physical processes such as accretion and winds occur. With high spectral and angular resolution, we focus on studying the continuum and the HI Br gamma-emitting area of the Herbig star HD 58647. Methods. Using VLTI-GRAVITY, we conducted observations of HD 58647 with both high spectral and high angular resolution. Thanks to the extensive uv coverage, we were able to obtain detailed images of the circumstellar environment at a sub-au scale, specifically capturing the continuum and the Br gamma-emitting region. Through the analysis of velocity-dispersed images and photocentre shifts, we were able to investigate the kinematics of the HI Br gamma-emitting region. Results. The recovered continuum images show extended emission where the disk major axis is oriented along a position angle of 14 degrees. The size of the continuum emission at 5-sigma levels is similar to 1.5 times more extended than the sizes reported from geometrical fitting (3.69 mas +/- 0.02 mas). This result supports the existence of dust particles close to the stellar surface, screened from the stellar radiation by an optically thick gaseous disk. Moreover, for the first time with GRAVITY, the hot gas component of HD 58647 traced by the Br gamma has been imaged. This allowed us to constrain the size of the Br gamma-emitting region and study the kinematics of the hot gas; we find its velocity field to be roughly consistent with gas that obeys Keplerian motion. The velocity-dispersed images show that the size of the hot gas emission is from a more compact region than the continuum (2.3 mas +/- 0.2 mas). Finally, the line phases show that the emission is not entirely consistent with Keplerian rotation, hinting at a more complex structure in the hot gaseous disk.

Abstract
The need for software developers is growing in a world where software systems play multiple roles in our daily lives. Due to the mental nature of their work, we are driven to address their needs. The concept of developer experience (DX) was defined as an extension of user experience, focusing on the dual role developers have as users and creators. This paper proposes a pattern language that can assist developers in improving their developer experience. In addition, we present a selection of patterns that focus on the cognitive dimension of the mind: Infrastructure Alignment, Adeqate Skills, It Takes A Village, Learning From A Master, Written Knowledge, and Practice Makes Perfect.