“Peradectoids” are among the most discussed extinct metatherians, primarily due to their uncertain affinities. Among South American localities, the Itaboraí Basin (late Paleocene-early Eocene), southeastern Brazil, preserves a minimum of five genera and seven species of putative “peradectoids”. Among them, a small-sized taxon, Lonchotrigonatus osvaldoi gen. et sp. nov., is described based on dental features. A phylogenetic analysis recovered it, other Itaboraí “peradectoids” (Bergqvistherium and Procaroloameghinia), and the Australian Archaeonothos within a clade, here informally named the southern peradectoid clade. These taxa did not form a clade with Peradectidae, which was also not recovered as a clade. The analysis suggests a late Campanian maximum origin for the clade comprising Peradectidae and Sudameridelphia. The cf. “Peradectes” austrinum from Tiupampa has a similar dental pattern to the ancestral lineage of Sudameridelphia, with the latter evolving from a common ancestor with a broad stylar shelf, straight centrocrista, and subequal paracone and metacone. Southern peradectoids share more dental features with notometatherians such as “herpetotheriids” than with northern “peradectoids”. Multiple South American clades comprise the early Eocene Australian fauna from Tingamarra. The early southern peradectoids occupied the role of generalized faunivores (insectivores-carnivores), especially at Itaboraí and Tingamarra, with Lonchotrigonatus and Archaeonothos as small-sized predators.
The structure of metacommunities has been attributed mainly to local (e.g., abiotic conditions and biotic interactions) and spatial factors (e.g., dispersal limitation and mass effect). However, our knowledge of the relative roles of these factors in structuring metacommunities at large spatial extents is unknown, especially using fine-grained data. Using a large data set from lakes covering the continental United States of America and encompassing phytoplankton, zooplankton, and macroinvertebrate communities, I assessed the relative importance of local environmental factors, climatic, and spatial variables using variance partitioning procedures. The phytoplankton metacommunity exhibited a strong spatial structure, whereas the zooplankton and macroinvertebrates metacommunities were mainly related to spatially structured environmental variables. In general, these results did not align with the expectations that small-bodied communities—with high dispersal ability—would be mainly related to local environmental factors and that relatively large-bodied communities – with low dispersal ability—would be associated primarily with spatial processes.
Air temperature is a critical climatic variable for agricultural production, influenced by multiple environmental factors and exhibiting pronounced spatial variability. In large agricultural regions of Brazil, its characterization is constrained by the low density and uneven distribution of meteorological stations. Despite the increasing applications of deep learning artificial neural networks, the importance of variable selection and model complexity at the monthly scale remains unclear in the Central-West region of Brazil. This study evaluated the applicability of deep learning models to estimate monthly maximum (Tmax), mean (Tm), and minimum (Tmin) air temperatures using long-term surface meteorological data from 81 weather stations covering the period 1990–2020. Nine explanatory variable scenarios (S1–S9), combining geographic and meteorological predictors, were assessed using deep learning architectures with different hidden layer configurations (M1, M2, and M3), and model performance was evaluated using training, validation, and test datasets. The results indicate that scenarios S1, S2, S3, S4, and S6 yielded more consistent estimates across months and network configurations, with a larger proportion of models achieving R² ≥ 70
In this work, a new sulfamerazine-based Ni complex was synthesized, namely tris(ethylenediamine-κ2N, N’)-nickel(II) bis(sulfamerazinate) hydrate (abbreviated as compound (I) herein), and characterized by single-crystal X-ray diffraction. Compound (I) crystallizes in the monoclinic C2/c space group. A detailed Hirshfeld surface (HS) analysis of (I) showed that its crystal structure is stabilized by the presence of O─H∙∙∙O, O─H∙∙∙N, N─H∙∙∙O and N─H∙∙∙N H-bonds, in addition to C─H∙∙∙H─C and C─H···π intermolecular interactions. The theoretical modeling revealed the significant influence of the crystalline environment, with a molecular dipole moment increase of 20.7
Communication barriers between Deaf patients and healthcare professionals remain a critical challenge in ensuring equitable medical care. This study examines the application of immersive technologies to facilitate anamnesis processes in Brazilian Sign Language (Libras), to improve accessibility and autonomy for Deaf individuals in medical settings. We conducted a systematic mapping of immersive applications designed for the Deaf community, which informed the development of two augmented reality–based solutions: one tailored for magnetic resonance imaging anamnesis and another for pupillometry examinations. Both applications enable interaction through Libras, hand gestures, and touch inputs, avoiding reliance on spoken or written language. To validate these tools, we carried out a usability evaluation with 27 Deaf participants using SUS-Libras, a culturally adapted version of the System Usability Scale. Results indicated an average score of approximately 55 points, classified as “OK” on the adjective rating scale, suggesting a satisfactory though improvable usability perception. No significant differences were found between the two applications, and demographic factors such as age, gender, education, and exposure time to Libras showed no predictive effect on usability outcomes. The research contributes to inclusive design practices and provides a foundation for future studies that extend immersive technologies to other medical scenarios.
