Abstract
Cities in Spain use to be overgrown around old towns (preroman, roman and medieval) constructed on topographic defensive heights of singular geological features. In the upper Guadalquivir valley, a tabular body of Miocene sediments has been eroded forming mesas where most of its population has been living since middle age. As the towns grew, new neighborhoods settled towards the edges and cliffs of these mesas, in areas with high probabilities of instability. The town of Arjona is a good example of this geological-urbanistic setup, located on the tabular hill formed by clay marls topped by bioclastic limestones that protect it from erosion. Modern buildings from few sectors of the town show important cracks, even the 16th century bell-tower has a 4º inclination indicating problems in the foundations. Multi-temporal SAR interferometry (MT-InSAR) is a powerful technique to derive displacement time series over coherent targets on the Earth associated with geophysical or structural instabilities phenomena. In this work we use MT-InSAR with Sentinel-1 data to reveal that, at present day, the periphery of Arjona is active, being recognized a large landslide in the south side of this mesa town which affects buildings and civil infrastructures. In addition, field work is being carried out to investigate the sources of these instabilities.

Abstract
This study presents principal component analysis (PCA) intra-subject variability of lower limb surface electromyography (sEMG) at different muscle stretch-shortening cycle (SSC). Several key steps are presented on the research of muscle force production for human in-vivo and noninvasive studies as well as on SSC contribution at gait, run, and jump with the need for separation of muscle and tendon behavior. Complexity and unpredicted multiple muscle actuation are highlighted with the need for extraction of PCA components from muscle stretch-shortening cycle sEMG, namely on lower limb stereotyped muscle patterns assessed on standard maximum vertical jump (MVJ). The purpose of this study is to apply PCA to sEMG linear envelopes of lower limb selected muscles at different MVJ, to detect lower number of components explaining maximum sEMG variability, representative of low dimensional signal control on muscles synergies. Different MVJ were assessed with subject specific PCA of lower limb sEMG during Counter Movement Jump (CMJ), Drop Jump (DJ), and Squat Jump (SJ). Intra-subject variability of sEMG PCA allowed the detection of two components explaining maximum variability with different profiles and muscle grouping at CMJ, DJ, and SJ. First component (PC1), representing larger signal variability, presented higher value at SJ and DJ than CMJ, with the need for a higher number of PC's to explain the same cumulative percentual variance at CMJ than DJ and SJ. Comparison with intra-subject linear (r) and cross-correlation (CCr) presented higher r and CCr at SJ and DJ than CMJ, with higher paired correlations at the muscles grouped on the same component. Comparison of intra-subject analysis with previous study on same subject single trial allowed subject-specific generalization of the preceding results.

Abstract
This paper aims to analyze the negative perception about the ability to generate value from a Governance System (GS). A model that would explain the reason for the less positive perception regarding the ability to generate value from the GS of the organizations, from the analysis of the relationship between the constructs Hybridism, GS, Accountability and Perception of Value based on IR, was proposed and validated with structural equation modeling (SEM), based on 658 responses from professionals of Brazilian organizations from the public, private and non-profit sectors. It is suggested that conflicts related to organizational hybridism negatively influence the results orientation of the GS, which in turn influences the imbalance of its Accountability. As a result of the GS's loss of results orientation, and considering the IR capitals in the disclosure of results, there is a negative perception of the GS's ability to add value to the results.

Abstract
With the greater awareness of climate change, the exponential expansion in the world population's energy needs, and other factors, many countries are producing and using renewable energy sources. However, this type of energy comes with a high cost associated with operation and maintenance. The importance of predictive maintenance in this area is growing, providing valuable insights for strategic decision-making. This paper aims to detect failures in wind turbines early. In our first approach, we considered the Page-Hinkley Test with a sliding window on the different vital components' temperature as a fault detection method. The second approach involved moving averages methods for forecasting the temperature of the different components. Our results showed that both methods could detect failures at least three days before and one day after the failure occurs.

Abstract
A growing interest in ocean exploration for scientific and commercial research has been shown, mainly due to the technological developments for maritime and offshore industries. The use of Autonomous surface vehicles (ASV) have a promising role to revolutionize the transportation, monitorization, operation and maintenance areas, allowing to perform distinct task from offshore assets inspection to harbor patrolling. This work presents SENSE, an autonomouS vEssel for multi-domaiN inSpection and maintEnance. It provides an open-source hardware and software architecture that is easy to replicate for both research institutes and industry. This is a multi-purpose vehicle capable of acquiring multi-domain data for inspecting and reconstructing maritime infrastructures. SENSE provides a research platform which can increase the situational awareness capabilities for ASVs. SENSE full configuration provides multimodal sensory data acquired from both domains using a Light Detection And Ranging (LiDAR), a stereoscopic camera, and a multibeam echosounder. In addition, it supplies navigation information obtained from a real-time kinematic satellite navigation system and inertial measurement units. Moreover, the tests performed at the harbor of Marina de Leca, at Porto, Portugal, resulted in a dataset which captures a fully operational harbor. It illustrates several conditions on maritime scenarios, such as undocking and docking examples, crossings with other vehicles and distinct types of moored vessels. The data available represents both domains of the maritime scenario, being the first public dataset acquired for multi-domain observation using a single vehicle. This paper also provides examples of applications for navigation and inspection on multi-domain scenarios, such as odometry estimation, bathymetric surveying and multi-domain mapping.

Abstract
In the last few decades, Portugal has witnessed an extraordinary quantitative and qualitative transformation in housing provision. The pace of housing construction was so extensive that the contemporary real estate market is currently characterized by an excessive supply, vis-a-vis the resident population. In this study, we discuss the impact of the financial process on the housing sector in comparison with tenancy. We consider transaction prices of the housing assignments, either through acquisition or through tenancy. The recent shock resulting from the pandemic situation did not slow down house prices but caused a slight drop in rents. The model used proposes to analyze the fluctuations in prices and rents in the face of external shocks. In the residential market, the estimation is complex due to the many heterogeneous attributes of residential assets. Non-fluctuating variables, such as size, location, and external demand for homes, explain a large part of the variation in price levels included in the model.