Merging trait-based ecology and regime shift theory to anticipate community responses to warming.

Anthropogenic warming is altering species abundance, distribution, physiology, and more. How changes observed at the species level alter emergent community properties is an active and urgent area of research. Trait-based ecology and regime shift theory provide complementary ways to understand climate change impacts on communities, but these two bodies of work are only rarely integrated. Lack of integration handicaps our ability to understand community responses to warming, at a time when such understanding is critical. Therefore, we advocate for merging trait-based ecology with regime shift theory. We propose a general set of principles to guide this merger and apply these principles to research on marine communities in the rapidly warming North Atlantic. In our example, combining trait distribution and regime shift analyses at the community level yields greater insight than either alone. Looking forward, we identify a clear need for expanding quantitative approaches to collecting and merging trait-based and resilience metrics in order to advance our understanding of climate-driven community change.

Testing the Acceptability and Usability of an AI-Enabled COVID-19 Diagnostic Tool Among Diverse Adult Populations in the United States.

BACKGROUND AND OBJECTIVES: Although at-home coronavirus disease-2019 (COVID-19) testing offers several benefits in a relatively cost-effective and less risky manner, evidence suggests that at-home COVID-19 test kits have a high rate of false negatives. One way to improve the accuracy and acceptance of COVID-19 screening is to combine existing at-home physical test kits with an easily accessible, electronic, self-diagnostic tool. The objective of the current study was to test the acceptability and usability of an artificial intelligence (AI)-enabled COVID-19 testing tool that combines a web-based symptom diagnostic screening survey and a physical at-home test kit to test differences across adults from varying races, ages, genders, educational, and income levels in the United States. METHODS: A total of 822 people from Richmond, Virginia, were included in the study. Data were collected from employees and patients of Virginia Commonwealth University Health Center as well as the surrounding community in June through October 2021. Data were weighted to reflect the demographic distribution of patients in United States. Descriptive statistics and repeated independent t tests were run to evaluate the differences in the acceptability and usability of an AI-enabled COVID-19 testing tool. RESULTS: Across all participants, there was a reasonable degree of acceptability and usability of the AI-enabled COVID-19 testing tool that included a physical test kit and symptom screening website. The AI-enabled COVID-19 testing tool demonstrated overall good acceptability and usability across race, age, gender, and educational background. Notably, participants preferred both components of the AI-enabled COVID-19 testing tool to the in-clinic testing. CONCLUSION: Overall, these findings suggest that our AI-enabled COVID-19 testing approach has great potential to improve the quality of remote COVID testing at low cost and high accessibility for diverse demographic populations in the United States.

The emergent coordination of cognitive function.

1/f scaling has been observed throughout human physiology and behavior, but its origins and meaning remain a matter of debate. Some argue that it is a byproduct of ongoing processes in the brain or body and therefore of limited relevance to psychological theory. Others argue that 1/f scaling reflects a fundamental aspect of all physiological and cognitive functions, namely, that they emerge in the balance of independent versus interdependent component activities. In 4 experiments, series of key-press responses were used to test between these 2 alternative explanations. The critical design feature was to take 2 measures of each key-press response: reaction time and key-contact duration. These measures resulted in 2 parallel series of intrinsic fluctuations for each series of key-press responses. Intrinsic fluctuations exhibited 1/f scaling in both reaction times and key-contact durations, yet the 2 measures were uncorrelated with each other and separately perturbable. These and other findings indicate that 1/f scaling is too pervasive to be idiosyncratic and of limited relevance. It is instead argued that 1/f scaling reflects the coordinative, metastable basis of cognitive function.