Multiscale analysis on otolith structural features reveals differences in ontogenesis and sex in Merluccius merluccius in the western Adriatic Sea.

Otolith biomineralization results from biochemical processes regulated by the interaction of internal (physiological) and external (environmental) factors which lead to morphological and ultrastructural variability at intra- and interspecific levels. The aim of this study was to conduct a multi-scale analysis of the sagittal otoliths of the Merlucius merlucius (European hake) from the western Adriatic Sea in order to correlate otolith features with fish ontogeny and sex. We show that otoliths of sexually undifferentiated (non-sexed) individuals having a fish body total length (TL) less than 15 cm had faster growth in length, width, area, perimeter, volume and weight and a higher amount of organic matrix compared with otoliths of sexually differentiated individuals (females and males) having a fish size range of 15-50 cm. Most importantly, with increasing fish TL, female saccular otoliths contained a higher number of protuberances and rougher surface compared with male specimens, which showed more uniform mean curvature density. The differences between females and males discovered in this study could be associated with fish hearing adaptation to reproductive behavioural strategies during the spawning season. The outcomes of this research provide insights on how size and sex-related variations in otolith features may be affected by fish ecological and behavioural patterns.

Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.