ABSTRACT The first mammaliaforms emerged in the Late Triassic, but their exact origins remain unclear due to the scarcity of fossils from this period. One of the earliest diverging mammaliaform groups, the order Docodonta, became unusually ecomorphologically diverse compared with other early mammals, and this may be connected to the possession of complex molar cusp morphology. The specimen described here, found in the Rhætelv Formation of the Kap Stewart Group (Rhaetian–Sinemurian) of central East Greenland, provides novel information on docodontan origins and evolution, as well as key biogeographic insights into early mammal dispersal. Nujalikodon cassiopeiae gen. et sp. nov. is the first mammaliaform found in the Rhætelv Formation, and is likely to be Early Jurassic (Hettangian) in age. Comprising an incomplete dentary with a single preserved molar, it was visualized using micro-computed tomography; the molar bears similarities to the putative early docodontan Delsatia, and docodontan Dobunnodon. Phylogenetic analysis places Nujalikodon cassiopeiae as a basal member of Docodonta or a close sister taxon, making it one of the oldest definitive docodontans and pushing the origin of the group back to at least the Early Jurassic. It provides insights into the development of docodontan dental complexity, a key factor in their ecological diversification during the Middle to Late Jurassic. Its presence in Greenland supports the hypothesis that docodontans originated in the region now comprising Europe and Greenland before dispersing across the rest of Laurasia.

The teachers’ central role in technology integration and the challenges of that integration emphasize the need for a deeper understanding about the teachers’ knowledge required to teach with technology. Based on previous work and a systematic literature review, we identified three knowledge models often used: TPACK, KTMT and PTK. The goal of this paper is to discuss the similarities and differences between these knowledge models and present a Global Model. This Global Model is not a new model. On the contrary, it is a model developed based on the existing models and intending to integrate in a single model the knowledge domains considered in the different existing models. The Global Model highlights the common domains considered and the common roots for the three models, but it also makes explicit the differences, mostly related to the understanding of the domains or even to the domains considered, and also to the way how the knowledge’s development is conceived.

Accurate blast models are essential for disaster management and emergency preparedness. Semi-empirical methods, which rely on free-field assumptions, struggle to provide precise data for complex building shapes because they ignore shock wave reflections. This research numerically investigates the effects of an explosion on a large building of complex geometrical configuration using blastFoam, estimating the façade damage and assessing risks to occupants. To evaluate the importance of accurately modelling the building’s geometry, four levels of detail were considered. Additionally, simulations were also performed using the Load Blast Enhanced (LBE) method from LS-DYNA to compare the estimates of this faster semi-empirical approach with those obtained through CFD analyses. The findings reveal that simpler CFD models are adequate for façade analysis and injury assessment around the building but fall short for predicting injury distribution within interior spaces or between buildings. The LBE underestimates both structural damage and human injury levels, while detailed CFD highlights the importance of accounting for interior walls and windows to enhance blast pressure predictions.

In this work, fully patterned zinc tin oxide (ZTO) memristors are introduced using inkjet printing. By targeting a scalable, solution-based fabrication approach, highly stable devices with excellent reproducibility and minimal variability are achieved, using ZTO as the active layer, silver (Ag) as the top electrode, and molybdenum as the bottom electrode. The use of sustainable materials like ZTO enhances scalability and environmental compatibility, paving the way for next-generation, low-power neuromorphic computing. The devices successfully fulfill the fundamental criteria for in materia implementation of physical reservoir computing (PRC), including nonlinearity and fading memory property. The devices are successfully trained for classification tasks with MNIST handwritten dataset, achieving 89.4% accuracy and 86.5% by processing 4-bit and 5-bit input temporal sequences. The integration of printed memristors into hardware-based PRC architecture simplifies training complexity, making them particularly advantageous for energy-efficient, wearable AI systems.

The fundamental value of universal nomenclatural systems in biology is that they enable unambiguous scientific communication. However, the stability of these systems is threatened by recent discussions asking for a fairer nomenclature, raising the possibility of bulk revision processes for “inappropriate” names. It is evident that such proposals come from very deep feelings, but we show how they can irreparably damage the foundation of biological communication and, in turn, the sciences that depend on it. There are four essential consequences of objective codes of nomenclature: universality, stability, neutrality, and transculturality. These codes provide fair and impartial guides to the principles governing biological nomenclature and allow unambiguous universal communication in biology. Accordingly, no subjective proposals should be allowed to undermine them.

Carbohydrate-binding-modules (CBMs) are discrete auxiliary protein modules with a non-catalytic carbohydrate-binding function and that exhibit a great diversity of binding specificities. CBMcarb-DB is a curated database that classifies the three-dimensional structures of CBM–carbohydrate complexes determined by single-crystal X-ray diffraction methods and solution NMR spectroscopy. We designed the database architecture and the navigation tools to query the database with the Protein Data Bank (PDB), UniProtKB, and GlyTouCan (universal glycan repository) identifiers. Special attention was devoted to describing the bound glycans using simple graphical representation and numerical format for cross-referencing to other glycosciences and functional data databases. CBMcarb-DB provides detailed information on CBMs and their bound oligosaccharides and features their interactions using several open-access applications. We also describe how the curated information provided by CBMcarb-DB can be integrated with AI algorithms of 3D structure prediction, facilitating structure–function studies. Also in this chapter, we discuss the exciting convergence of CBMcarb-DB with the glycan array repository, which serves as a valuable resource for investigating the specific binding interactions between glycans and various biomolecular targets. The interaction of the two fields represents a significant milestone in glycosciences. CBMcarb-DB is freely available at https://cbmdb.glycopedia.eu/ and https://cbmcarb.webhost.fct.unl.pt.

The structural and chemical diversity of β-glucans is reflected on the variety of essential biological roles tackled by these polysaccharides. This natural heterogeneity requires an elaborate assortment of enzymatic mechanisms to assemble, degrade or modify, as well as to extract their full biotechnological potential. Recent metagenomic efforts have provided an unprecedented growth in potential new biocatalysts, most of which remain unconfirmed or uncharacterized. Here we report the first biochemical and structural characterization of two bacterial β-glucanases from the recently created glycoside hydrolase family 157 (LaGH157 and BcGH157) and investigate their molecular basis for substrate hydrolysis. Structural analysis by X-ray crystallography revealed that GH157 enzymes belong to clan GH-A, possessing a (β/α)8-barrel fold catalytic domain, two β-sandwich accessory domains and two conserved catalytic glutamates residues, with relative positions compatible with a retaining mechanism of hydrolysis. Specificity screening and enzyme kinetics suggest that the enzymes prefer mixed-linkage glucans over β-1,3-glucans. Activity screening showed that both enzymes exhibit pH optimum at 6.5 and temperature optimum for LaGH157 and BcGH157 at 25 °C and 48 °C, respectively. Product analysis with HPAEC-PAD and LC-MS revealed that both enzymes are endo-1,3(4)-β-glucanases, capable of cleaving β-1,3 and β-1,4-linked glucoses, when preceded by a β-1,3 linkage. Moreover, BcGH157 needs a minimum of 4 subsites occupied for hydrolysis to occur, while LaGH157 only requires 3 subsites. Additionally, LaGH157 possesses exohydrolytic activity on β-1,3 and branching β-1,6 linkages. This unusual bifunctional endo-1,3(4)/exo-1,3–1,6 activity constitutes an expansion on our understanding of β-glucan deconstruction, with the potential to inspire future applications.