Abstract
Predicting the performance of a mixture is crucial to designing experiences in product development and formulation research. In this work, an application, MDesign, is proposed to construct models in a mixture design with a practical, educational, and intuitive approach. Developed in MATLAB software, the standalone application aims to contribute to the study of mixtures through the definition of multivariate models of different orders, enabling their statistical analysis to verify the robustness of each of those models. Compared to the obtained results from other applications using data experiments published in the literature, the proposed application presents accurate results and good execution. MDesign can be considered an automatic, robust, and valuable tool to support the mixture design in an industrial context.

Abstract
In this paper, we describe a preliminary study on a multisensory music experience for people with hearing loss. Our main goal is to provide a music event through visual and tactile stimuli, granting a multisensory experience using haptic interfaces and taking advantage of visual feedback, vibrations and pressure to induce feelings. In this context, a mobile application was developed, allowing the user to interact with recorded audio samples that exploit vibrations to trigger emotions, such as fear, adrenaline, anxiety, suspense, drama, adventure, or even more complex moods like when dancing and relaxing. We thus describe our methodology (design, implementation and user assessment) for a preliminary study of a music experience based on a user-centered design approach. Indeed, we gathered promising results as the experience was considered effective and satisfying. We also uncovered some development issues to be addressed in future work, having to do with the use of specific hardware for providing a fully immersive experience. © 2022, Springer Nature Switzerland AG.

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.