Seawater desalination has been studied with interest due to the scarcity of fresh water for human consumption. Solar distillation is an old method; the productivity, energy consumption of the process and the cost of the desalinated water thus obtained depend on the efficiency achieved in each of the stages of these systems. The limited capacity to absorb solar radiation and transform it into useful heat for evaporation, interaction with the surrounding medium, and heat losses restrict the overall efficiency of the thermal process and productivity. Since the energy comes from solar radiation, the maximum productivity of this process will be constrained by the magnitude of the total solar radiation available in an area of the planet due to its geographic location, time of year and local climatic conditions. The processes of this energy will be thermodynamically limited by the heat transfer coefficients achieved in the equipment, the maximum value that the evaporation heat can reach, as long as the losses to the environment by convection and radiation are minimal. Comparative analyses of several proposed models, reported data of distillers, reported data of solar radiation that reach average values of up to 7.2–7.4 kwh/m² in some regions of the planet are presented and estimates are made for productivity of these equipments that they reach between 6.7 and 6.9 kg/m² day with a theoretical maximum efficiency of about 0.16 of the total solar radiation.

The high demand for quality healthcare services in Portugal is generating concerns about meeting the optimum number of healthcare professionals in the private sector, such as doctors and clinicians. Critical interventions are currently in progress, aiming to provide quality healthcare that will be accessible and sustainable through actionable retention strategies such as investing and developing human capital, introducing better conditions of service to attract and retain talent in the private healthcare sector, and prioritizing the needs of patients. The objective of this study is to understand which factors promote the migration of physicians from the public to the private sector according to the theoretical assumptions of incentives. In this context, a phenomenological study was carried out, using semi-structured interviews with fifteen physicians working in the private health network. Content analysis was done using NVivo 12. The results indicate that performance evaluation in the private sector exists but has no alignment with incentives. The condition makes the private healthcare sector unattractive, however, other policies of remuneration remain promising. Current proposals that could revive the image of the sector include collective decision-making and strong labour relations advocacy for physicians in the private sector.

Tidal sea level variations in the Mediterranean basin, although altered and amplified by resonance phenomena in confined sub-basins (e.g., Adriatic Sea), are generally confined within 0.5 meters and exceptionally up to 1.5 meters. Here we explore the possibility of retrieving sea level measurements using data from GNSS antennas on duty for ground motion monitoring and analyze the spectral outcomes of such distinctive measurements. We estimate one year of GNSS data collected on the Mediterranean coasts in order to get reliable sea level data from all publicly available data and compare it with collocated tide gauges. A total of eleven stations were suitable for interferometric analysis (as of 2021), and all were able to supply centimeter-level sea level estimates. The spectra in the tidal frequency windows are remarkably similar to tide gauge data. We find that the O₁ and M₂ diurnal and semidiurnal tides and MK₃, MS₄ shallow sea water tides may be disturbed by aliasing effects.

Recognizing the discipline category of the abstract text is of great significance for automatic text recommendation and knowledge mining. Therefore, this study obtained the abstract text of social science and natural science in the Web of Science 2010-2020, and used the machine learning model SVM and deep learning model TextCNN and SCI-BERT models constructed a discipline classification model. It was found that the SCI-BERT model had the best performance. The precision, recall, and F1 were 86.54%, 86.89%, and 86.71%, respectively, and the F1 is 6.61% and 4.05% higher than SVM and TextCNN. The construction of this model can effectively identify the discipline categories of abstracts, and provide effective support for automatic indexing of subjects.