Abstract
Solar energy will contribute to global economic growth, increasing worldwide photovoltaic (PV) solar energy production. More recently, one of the outstanding energy achievements of the last decade has been the development of floating photovoltaic panels. These panels differ from conventional (ter-restrial) panels because they occupy space in a more environmen-tally friendly way, i.e., aquatic areas. In contrast, land areas are saved for other applications, such as construction or agriculture. Developing autonomous inspection systems using unmanned aerial vehicles (UAV s) represents a significant step forward in solar PV technology. Given the frequently remote and difficult-to-access locations, traditional inspection methods are no longer practical or suitable. Responding to these challenges, an in-novative inspection framework was developed to autonomously inspect photovoltaic plants (offshore) with a Vertical Takeoff and Landing (VTOL) UAV. This work explores two different methods of autonomous aerial inspection, each adapted to specific scenarios, thus increasing the adaptability of the inspection process. During the flight, the aerial images are evaluated in real-time for the autonomous detection of the photovoltaic modules and the detection of possible faults. This mechanism is crucial for making decisions and taking immediate corrective action. An offshore simulation environment was developed to validate the implemented system.

Abstract
The eDNA autonomous biosampler results from a line of research aimed at developing systems for sampling and collecting marine biological data, and for collecting environmen-tal DNA. Environmental DNA is a tool that has been increasingly used in the biological monitoring of aquatic environments, as it is a non-invasive method with very promising results when it comes to assessing biological diversity. In this sense, the automation of this method has the potential to greatly increase the temporal and spatial resolution of current biological monitoring programs in aquatic environments. The system has been developed in a partnership between research teams at the Centre for Robotics and Autonomous Systems (CRAS - INESC TEC) and CIIMAR and has been tested in multiple operational scenarios, including the Arctic, where it was attached to the AUV IRIS. © 2024 IEEE.

Abstract
The Czech Republic is home to the Hranice Abyss, the world's deepest natural underwater cave, a site extensively explored by a dedicated team of divers from a speleology group. Over the years, numerous studies have been conducted to unravel the cave's mysteries, delving into fields such as biology, hydrogeology, and geology. Mapping a cave of such vast dimensions and staggering depth poses formidable challenges, making the task hazardous, demanding, and timeintensive for a limited team of divers. In July 2022, the UNEXUP project was invited to explore and map the cave with its robot (UXl-neo), which contains many acoustic and optical sensors, used for navigation, localization, and mapping. Its unique control and dynamics allow the robot to successfully navigate through caves and flooded mines. This paper delves into the specifics of the six days of mission dives, offering insights into the mapping process, and presenting some of the results obtained from the entire cave. © 2024 IEEE.

Abstract
Objectives Space, an extreme environment, poses significant challenges to human physiology, including adverse effects on oral health (e.g., increase of periodontitis prevalence, caries, tooth sensitivity). This study investigates the differences in oral health routines and oral manifestations among analog astronauts during their daily routines and simulated space missions conducted on Earth. Materials and methods This research focused on scientist-astronaut candidates of the International Institute for Astronautical Sciences (IIAS) and analog astronauts from other institutions. The study used a cross-sectional methodology with a descriptive component. A total of 16 participants, comprising individuals aged between 21 and 55 years, were invited to complete an online questionnaire. A comparison was made between the subjects' oral hygiene practices in everyday life (designated as Earth in this research) and their oral hygiene routines during their space analog missions. Results (i) Toothbrushing duration was mostly 1-3 minutes (n = 13; 81.30% on Earth; n = 11; 68.80% on a mission); (ii) time spent was the greatest difficulty in maintaining oral hygiene routine on a mission (n = 9; 53,6%); (iii) There were more experienced oral symptoms on Earth (n = 12; 75%) than on mission (n = 7; 43.80%); (iv) The most frequent frequency of oral check-ups was > 12 months (n = 6; 37,5%); (v) Oral health materials were scarce on the mission (n = 9; 56.30%); (vi) For the majority, personal oral hygiene was classified as good (n = 9; 56.30% on Earth; n = 7; 43.80% on the mission). Conclusion and Clinical relevance This research contributes to increasing knowledge of oral hygiene measures in extreme environments, but further research is needed as this topic remains relatively understudied. This study represents an initial contribution to oral health in analog space missions, aiming to propose guidelines for future missions, including deep space missions and expeditions to extreme environments.

Abstract
Solar wind forecasting is a core component of Space Weather, a field that has been the target of many novel machine-learning approaches. The continuous monitoring of the Sun has provided an ever-growing ensemble of observations, facilitating the development of forecasting models that predict solar wind properties on Earth and other celestial objects within the solar system. This enables us to prepare for and mitigate the effects of solar wind-related events on Earth and space. The performance of some simulation-based solar wind models depends heavily on the quality of the initial guesses used as initial conditions. This work focuses on improving the accuracy of these initial conditions by employing a Recurrent Neural Network model. The study's findings confirmed that Recurrent Neural Networks can generate better initial guesses for the simulations, resulting in faster and more stable simulations. In our experiments, when we used predicted initial conditions, simulations ran an average of 1.08 times faster, with a statistically significant improvement and reduced amplitude transients. These results suggest that the improved initial conditions enhance the numerical robustness of the model and enable a more moderate integration time step. Despite the modest improvement in simulation convergence time, the Recurrent Neural Networks model's reusability without retraining remains valuable. With simulations lasting up to 12 h, an 8% gain equals one hour saved per simulation. Moreover, the generated profiles closely match the simulator's, making them suitable for applications with less demanding physical accuracy.

Abstract
Composites of poly(vinyl alcohol) (PVA) in the shape of braids, in combination with crystals of hydroxyapatite (HAp), were analyzed to perceive the influence of this bioceramic on both the quasi-static and viscoelastic behavior under tensile loading. Analyses involving energy-dispersive X-ray spectroscopy (EDS) and scanning electron microscopy (SEM) allowed us to conclude that the production of a homogeneous layer of HAp on the braiding surface and the calcium/phosphate atomic ratio were comparable to those of natural bone. The maximum degradation temperature established by thermogravimetric analysis (TGA) showed a modest decrease with the addition of HAp. By adding HAp to PVA braids, an increase in the glass transition temperature (Tg) is noticed, as demonstrated by dynamic mechanical analysis (DMA) and differential thermal analysis (DTA). The PVA/HAp composite braids' peaks were validated by Fourier transform infrared (FTIR) spectroscopy to be in good agreement with common PVA and HAp patterns. PVA/HAp braids, a solution often used in the textile industry, showed superior overall mechanical characteristics in monotonic tensile tests. Creep and relaxation testing showed that adding HAp to the eight and six-braided yarn architectures was beneficial. By exhibiting good mechanical performance and most likely increased biological qualities that accompany conventional care for bone applications in the fracture healing field, particularly multifragmentary ones, these arrangements can be applied as a fibrous fixation system.