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Members of the genus Centris Fabricius (Hymenoptera: Apoidea: Anthophila) constitute a significant component of the Neotropical (including insular) bee fauna, exhibiting high species richness, a moderate to large body size, and extensive interactions with various important plant groups. Females of most species possess specialized morphology adapted for collecting oils from flowers. This study documents the presence of the genus in Cuba, recognizing six species: C. aethiops Cresson, C. cornuta Cresson, C. fulviventris Cresson, C. poecila Lepeletier, C. taina Genaro and Breto new species, and C. tarsata F. Smith. Detailed information is provided for each species, encompassing a diagnosis, natural history, floral associations, seasonal occurrence, and distribution. Centris taina new species is described from Cuba, based on both sexes, which were previously misidentified as C. versicolor (Fabr.) for females and C. fasciatus F. Smith for males due to sexual dimorphism. Centris tarsata is reported as a new national record for Cuba, possibly introduced by humans from South America and now established and widely distributed across the entire island. A key to differentiate the Cuban species of Centris is presented.
ZooBank registration. urn:lsid:zoobank.org:pub:257916DF-2129-4694-876C-49C858046BF6
The two-particle momentum correlation functions between charm mesons (D∗± and D±) and charged light-flavor mesons (π± and K±) in all charge-combinations are measured for the first time by the ALICE Collaboration in high-multiplicity proton-proton collisions at a center-of-mass energy of s√=13 TeV. For DK and D∗K pairs, the experimental results are in agreement with theoretical predictions of the residual strong interaction based on quantum chromodynamics calculations on the lattice and chiral effective field theory. In the case of Dπ and D∗π pairs, tension between the calculations including strong interactions and the measurement is observed. For all particle pairs, the data can be adequately described by Coulomb interaction only, indicating a shallow interaction between charm and light-flavor mesons. Finally, the scattering lengths governing the residual strong interaction of the Dπ and D∗π systems are determined by fitting the experimental correlation functions with a model that employs a Gaussian potential. The extracted values are small and compatible with zero.
For genus g=r(r+1)2+1, we prove that via the forgetful map, the universal Prym-Brill-Noether locus Rrg has a unique irreducible component dominating the moduli space Rg of Prym curves.
Can prediction error explain predictability effects on the N1 during picture-word verification?
(2024)
Do early effects of predictability in visual word recognition reflect prediction error? Electrophysiological research investigating word processing has demonstrated predictability effects in the N1, or first negative component of the event-related potential (ERP). However, findings regarding the magnitude of effects and potential interactions of predictability with lexical variables have been inconsistent. Moreover, past studies have typically used categorical designs with relatively small samples and relied on by-participant analyses. Nevertheless, reports have generally shown that predicted words elicit less negative-going (i.e., lower amplitude) N1s, a pattern consistent with a simple predictive coding account. In our preregistered study, we tested this account via the interaction between prediction magnitude and certainty. A picture-word verification paradigm was implemented in which pictures were followed by tightly matched picture-congruent or picture-incongruent written nouns. The predictability of target (picture-congruent) nouns was manipulated continuously based on norms of association between a picture and its name. ERPs from 68 participants revealed a pattern of effects opposite to that expected under a simple predictive coding framework.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
Looking beyond ESG preferences: The role of sustainable finance literacy in sustainable investing
(2024)
We assess how sustainable finance literacy affects people’s sustainable investment behavior, using a pre-registered experiment. We find that an increase in sustainable finance literacy leads to a 4 to 5% increase in the probability of investing sustainably. This effect is moderated by sustainability preferences. In the absence of moderate sustainability preferences, any additional increase in sustainable finance literacy is at minimum irrelevant, and we find some evidence that it might even reduce sustainable investments. Our findings underscore the role of knowledge in shaping sustainable investment decisions, highlighting the importance of factors beyond sustainability preferences.
Korean immigrants have migrated to New Zealand over the past three decades in search of a happier and more balanced life. While they anticipated that their children would be integrated into New Zealand society, they have primarily settled in Korean ethnic enclaves. In this context, younger Korean New Zealanders have been exposed to and influenced by New Zealand’s national and Korean ethnic cultures. This study examined success beliefs and well-being among Korean youth in New Zealand with a Third Culture Kid background (TCK K-NZ) in comparison to Korean youth in Korea (K-Korean) and European New Zealand youth (Pākehā). Results indicated that TCK K-NZ youth endorsed extrinsic success similarly to K-Korean youth, but that valuing extrinsic success predicted lowered well-being only for K-Korean youth. Conversely, valuing intrinsic success predicted higher well-being across the three groups. Results also revealed that TCK K-NZ youth's well-being levels were between those of K-Korean and Pākehā youth, potentially influenced by different structural relations between success beliefs and well-being, as well as their position as “third culture kids” in New Zealand. This study contributes to understanding cultures' roles in formulating success beliefs and the relationship between success beliefs and well-being for Korean New Zealander youth.
We provide in this paper a comprehensive comparison of various transfer learning strategies and deep learning architectures for computer-aided classification of adult-type diffuse gliomas. We evaluate the generalizability of out-of-domain ImageNet representations for a target domain of histopathological images, and study the impact of in-domain adaptation using self-supervised and multi-task learning approaches for pretraining the models using the medium-to-large scale datasets of histopathological images. A semi-supervised learning approach is furthermore proposed, where the fine-tuned models are utilized to predict the labels of unannotated regions of the whole slide images (WSI). The models are subsequently retrained using the ground-truth labels and weak labels determined in the previous step, providing superior performance in comparison to standard in-domain transfer learning with balanced accuracy of 96.91% and F1-score 97.07%, and minimizing the pathologist's efforts for annotation. Finally, we provide a visualization tool working at WSI level which generates heatmaps that highlight tumor areas; thus, providing insights to pathologists concerning the most informative parts of the WSI.