With the escalating urbanization and intensified anthropogenic activities, a pervasive manifestation of global warming has become evident on a global scale. In this study, we analyzed the monthly temperature anomaly trends in comparison to the average of the recent hottest decade (2010-2019), for the two contrasting regions of Italy, witnessing Csa (temperate dry and hot summer), and Cfa (temperate no dry season hot summer) climate type based on Köppen-Geiger climate classification. Our findings reveal a consistently increased temperature in recent years. To ascertain the trends, a polynomial regression analysis was performed, elucidating both positive and negative trends for each month. Specifically, the Emilia Romagna (Cfa) region shows a positive trend for winter temperatures, contrasting with the trend observed for Lazio (Csa). This comprehensive analysis aids in comprehending the impacts of elevated intra-annual temperatures within different climatic regions. The insights derived from the study would help policymakers plan targeted climate-resilient green strategies, fostering sustainable development in the foreseeable future.

The study addresses the critical role of Land Surface Temperature (LST) in understanding the energy equilibrium of surfaces, particularly in urban areas facing heightened thermal stress due to global warming. Current open-source satellite data resolutions, while useful, lack precision for detailed urban analysis, necessitating the adoption of super-resolved LST. The study explores various downscaling algorithms, focusing on statistical regression, and emphasizes the importance of vegetation, built-up areas, and water bodies in temperature dynamics. The case study has been performed over an Italian city and examines the influence of land use indices on LST downscaling, proposing an ablation study to identify optimal predictive variables. Using multiple linear regression and satellite indices, the study aims to enhance accuracy while optimizing computational resources. The conclusion highlights the significance of refining downscaling models for improved temperature trend analysis at super-resolution, offering valuable insights for sustainable urban development and climate-resilient policies.

Tendon-driven continuum robots show promise for use in surgical applications as they can assume complex configurations to navigate along tortuous paths. However, to achieve these complex robot shapes, multiple segments are required as each robot segment can bend only with a single constant curvature. To actuate these additional robot segments, multiple tendons must typically be added on-board the robot, complicating their integration, robot control, and actuation. This work presents a method of achieving two curvatures in a single tendon-driven continuum robot segment through use of a novel magnetic locking mechanism. Thus, the need for additional robot segments and actuating tendons is eliminated. The resulting two curvatures in a single segment are demonstrated in two and three dimensions. Furthermore, the maximum magnetic field required to actuate the locking mechanism for different robot bending angles is experimentally measured to be 6.1 mT. Additionally, the locking mechanism resists unintentional unlocking unless the robot assumes a 0° bending angle and a magnetic field of 18.1 mT is applied, conditions which are not typically reached during routine use of the system. Finally, addressable actuation of two locking mechanisms is achieved, demonstrating the capability of producing multiple curvatures in a single robot segment.

Due to the continuous and flexible nature of continuum robot backbones and the infinite number of parameters required to represent them in configuration space, modeling them accurately and in real-time is challenging. While the constant curvature assumption provides a simple alternative, it is limited in its capabilities as it cannot account for external tip forces. In cases where the backbone deviates from the constant curvature backbone, Euler curves are an interesting alternative for modeling continuum robots. In this paper, we show that a linear approximation of the backbone curvature is sufficiently accurate for estimating the shape of a robot subject to external tip forces. Next, we propose a numerical static model for tendon-driven continuum robots experiencing in-plane external tip forces. In this model, we use Euler arc splines to circumvent the limitations of standard numerical integration schemes required to calculate these curves. The system reduces to solving two nonlinear equations, allowing fast approximation of the backbone shape. The proposed model is validated experimentally on a robot prototype. Average tip error of 3.07% of the robot length is obtained for an average computation time of 0.51 ms.