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This project has been dedicated to advance the way computational thinking is taught to engineering undergraduate students with a multitude of social identities. It is an expectation that with the understanding of the multiple factors that affect computational thinking skills development, students succeed in enculturating to the engineering professional practice. During the third year of this project, the first major result is the conclusion of the validation process of the Engineering Computational Thinking Diagnostic (ECTD) making use of exploratory and confirmatory factor analyses (EFA-CFA). Our validation showed that the ECTD questions cluster in one factor, what we call the computational thinking factor for engineers. Other validation statistical processes (i.e. correlations, regressions, ANOVA and t-tests) proved the predictability potential use of this tool in determining how well prepared students arrive to the engineering classroom and how their prior coding experience can determine their success in introductory coding engineering courses. The second major result is the revelation that the inequities caused by the many forms of privilege that some engineering students benefit from are being exacerbated by the integration of computational thinking into introductory engineering classes. Due to pandemic-related challenges in recruiting a representative sample of participants, the majority of the self-selected participants in our research identify with groups with disproportionately large participation in engineering (specifically White and Asian) and are academically successful in engineering. To respond to this challenge we are seeking to broaden our perspective by seeking participants with failing grades for a final round of data collection, although we are well aware that students in this group are often reluctant to participate in research. The fourth and last major result is related to the position of stress versus Artificial Intelligence (AI) perceptions, both part of the ECTD instrument. The position of stress questions involved perceived difficulty and confidence level after taking the ECTD. The artificial intelligence question asked the perceived impact of AI in students’ future career prospects. Preliminary analysis is suggesting that confidence level is correlated with AI positive perceptions. Although not part of the original NSF grant, we considered AI the natural evolution of computational thinking in the formation of engineers and plan to continue our work in this direction. 

Dense aggregations of serpulid worms were encountered in the Daymaniyat Islands (Gulf of Oman) from 10 to 20 m depth, over the period January–March, 2021. The species responsible for these aggregations belongs to the Filograna/Salmacina-complex (Annelida: Serpulidae). This species has been present in the area and observed along the Oman coastline, but high-density aggregates like this have not been reported before. The most probable cause of the aggregations, supported by field observations and Aqua-MODIS satellite data, was natural eutrophication with a subsequent algal bloom linked to the local winter monsoon. This observation emphasises the importance of documenting biodiversity and dynamics of reef communities along the Oman coastline. 

Metasurfaces have recently risen to prominence in optical research, providing unique functionalities that can be used for imaging, beam forming, holography, polarimetry, and many more, while keeping device dimensions small. Despite the fact that a vast range of basic metasurface designs has already been thoroughly studied in the literature, the number of metasurfacerelated papers is still growing at a rapid pace, as metasurface research is now spreading to adjacent fields, including computational imaging, augmented and virtual reality, automotive, display, biosensing, nonlinear, quantum and topological optics, optical computing, and more. At the same time, the ability of metasurfaces to perform optical functions in much more compact optical systems has triggered strong and constantly growing interest from various industries that greatly benefit from the availability of miniaturized, highly functional, and efficient optical components that can be integrated in optoelectronic systems at low cost. This creates a truly unique opportunity for the field of metasurfaces to make both a scientific and an industrial impact. The goal of this Roadmap is to mark this “golden age” of metasurface research and define future directions to encourage scientists and engineers to drive research and development in the field of metasurfaces toward both scientific excellence and broad industrial adoption.