The basic colour terms for black and white are studied in four archaic and two contemporary linguistic norms of the Chinese language. It is presented that studied Chinese linguistic norms use a common term for white and three different terms for black. It is suggested that the different basic colour terms for black might originate from different source languages. The study supports a panchronic language development instead of a diachronic one, and includes introductions to histories of the Chinese linguistic norms
The efficacy of animal signals is strongly influenced by the structure of the habitat in which they are propagating. In recent years, the habitat structure of temperate forests has been increasingly subject to modifications from foraging by white-tailed deer (
Odocoileus virginianus
). Increasing deer numbers and the accompanying browsing have been shown to alter vegetation structure and thus the foraging, roosting, and breeding habitats of many species. However, despite a large body of literature on the effects of vegetation structure on sound propagation, we do not yet know what impact deer browsing may have on acoustic communication. Here we used playback experiments to determine whether sound fidelity and amplitude of white noise, pure tones, and trills differed between deer-browsed and deer-excluded plots. We found that sound fidelity, but not amplitude, differed between habitats, with deer-browsed habitats having greater sound fidelity than deer-excluded habitats. Difference in sound propagation characteristics between the two habitats could alter the efficacy of acoustic communication through plasticity, cultural evolution or local adaptation, in turn influencing vocally-mediated behaviors (e.g. agonistic, parent-offspring, mate selection). Reduced signal degradation suggests vocalizations may retain more information, improving the transfer of information to both intended and unintended receivers. Overall, our results suggest that deer browsing impacts sound propagation in temperate deciduous forest, although much work remains to be done on the potential impacts on communication.
The relative timing of sleep and of eating within the circadian day is important for human health. Despite much data on sleep and a growing data set for eating, there remains a need for an interpretative framework for the understanding of this data for health decisions. This study provides a new statistical and machine learning analysis of more than 500 participants in the Daily24 project. From their data, and the analysis, we propose a framework for determining the classification of participants into different chronotypes and with that the ability to realize the potential impact of daily circadian habits on health. We propose that our resulting distribution curves could be used, similar to NHANES (National Health and Nutrition Examination Survey) data for pediatric growth, as a measure for circadian misalignment and used to help guide re-entrainment schedules.
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