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A CFL-type Condition and Theoretical Insights for Discrete-Time Sparse Full-Order Model Inference
No full textBeyond the target: source motivation and observer attributions in ostracism research
No full textOstracism research has largely focused on the role of the target. However, this perspective does not account for the significant roles played by two other parties in the dynamics of ostracism: the sources who decide to ostracize a target and the observers who may be uninvolved or side with either the target or the sources. Here, we argue that accounting for these two perspectives is important if one wants to arrive at a comprehensive picture of ostracism episodes. We present research on the reasons and motivations of the sources for ostracizing as well as research on factors that influence moral judgments and attributions of observers. Moreover, we suggest an agenda for future research that entails 1) linking the perspectives of targets, sources, and observers, 2) developing novel paradigms to study observers and sources, and 3) designing interventions that encourage sources and observers to detect and be mindful of the use of ostracism
Harmonized protocol for subfield segmentation in the hippocampal body on high-resolution in vivo MRI from the Hippocampal Subfields Group (HSG)
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Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors?
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Collecting, detecting and handling non-wear intervals in longitudinal light exposure data
No full textIn field studies using wearable light loggers, participants often need to remove the devices, resulting in non-wear intervals of varying and unknown duration. Accurate detection of these intervals is an essential step during data pre-processing. Here, we deployed a multi-modal approach to collect non-wear time during a longitudinal light exposure collection campaign and systematically compare non-wear detection strategies. Healthy participants (n = 26; mean age 28 ± 5 years, 14F) wore a near-corneal plane light logger for 1 week and reported non-wear events in three ways: pressing an "event marker" button on the light logger, placing it in a black bag, and using an app-based Wear log. Wear log entries, checked twice daily, served as ground truth for non-wear detection, showing that non-wear time constituted 5.4 ± 3.8% (mean ± SD) of total participation time. Button presses at the start and end of non-wear intervals were identified in >85.4% of cases when considering time windows beyond 1 min for detection. To detect non-wear intervals based on black bag use and lack of motion, we employed an algorithm that detects clusters of low illuminance and clusters of low activity. Performance was higher for illuminance (F1 = 0.78) than for activity (F1 = 0.52). Light exposure metrics derived from the full dataset, a dataset filtered for non-wear based on self-reports, and a dataset filtered for non-wear using the low illuminance clusters detection algorithm showed minimal differences. Our results highlight that while non-wear detection may be less critical in high-compliance cohorts, systematically collecting and detecting non-wear intervals is feasible and important for ensuring robust data pre-processing
