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Integrating remote Internet of Things (IoT) laboratories into project-based learning (PBL) in higher education institutions (HEIs) while exploiting the approach of technology-enhanced learning (TEL) is a challenging yet pivotal endeavor. Our proposed approach enables students to interact with an IoT-equipped lab locally and remotely, thereby bridging theoretical knowledge with practical application, creating a more immersive, adaptable, and effective learning experience. This study underscores the significance of combining hardware, software, and coding skills in PBL, emphasizing how IoTRemoteLab (the remote lab we developed) supports a customized educational experience that promotes innovation and safety. Moreover, we explore the potential of IoTRemoteLab as a TEL, facilitating and supporting the understanding and definition of the requirements of remote learning. Furthermore, we demonstrate how we incorporate generative artificial intelligence into IoTRemoteLab's settings, enabling personalized recommendations for students leveraging the lab locally or remotely. Our approach serves as a model for educators and researchers aiming to equip students with essential skills for the digital age while addressing broader issues related to access, engagement, and sustainability in HEIs. The practical findings following an in-class experiment reinforce the value of IoTRemoteLab and its features in preparing students for future technological demands and fostering a more inclusive, safe, and effective educational environment. [ABSTRACT FROM AUTHOR]

Early in the seventeenth century an aspiring dramatist called Arthur Wilson (1595-1652) sat down to write a play. Three of his plays were later performed on the London stage by [...]

The article discusses an anonymous dramatic fragment called 'Comedy of Stella and Alexis' found in Bodleian MS Douce 171. The author argues that the play was written by Arthur Wilson and was likely intended for domestic entertainment rather than public performance. The author suggests that the name 'Stella' in the play may be a reference to Penelope Devereux, who was the aunt of Wilson's employer and the inspiration for Philip Sidney's sonnet sequence, Astrophel and Stella. The article also explores the connection between Penelope Devereux and Philip Sidney and how the play may have been shaped to appeal to the Essex household. The author concludes that the play reflects the compositional practices of a burgeoning playwright and the nature of early modern private theater. [Extracted from the article]

Water storage changes in the soil can be observed on a global scale with different types of satellite remote sensing. While active or passive microwave sensors are limited to the upper few centimeters of the soil, satellite gravimetry can detect changes of terrestrial water storage (TWS) in an integrative way but it cannot distinguish between storage variations in different compartments or soil depths. Jointly analyzing both data types promises novel insights into the dynamics of subsurface water storage and of related hydrological processes. In this study, we investigate the global relationship of (1) several satellite soil moisture products and (2) non-standard daily TWS data from the GRACE and GRACE-FO satellite gravimetry missions on different time scales. The six soil moisture products analyzed in this study differ in post-processing and the considered soil depth. Level-3 surface soil moisture data sets of SMAP and SMOS are compared to post-processed Level-4 data products (surface and root zone soil moisture) and the ESA CCI multi-satellite product. On a common global 1 degree grid, we decompose all TWS and soil moisture data into seasonal to sub-monthly signal components and compare their spatial patterns and temporal variability. We find larger correlations between TWS and soil moisture for soil moisture products with deeper integration depths (root zone vs. surface layer) and for Level-4 data products. Even for high-pass filtered sub-monthly variations, significant correlations of up to 0.6 can be found in regions with large high-frequency storage variability. A time-shift analysis of TWS versus soil moisture data reveals the differences in water storage dynamics with integration depth. [ABSTRACT FROM AUTHOR]