Many airlines instituted social distancing practices to keep passengers safe during the pandemic. The practices include keeping the middle seats empty, reducing the number of passengers taking an apron bus from the terminal to the airplane, and prescribing that passengers maintain 1 m social distance of separation from other passengers in the aisle while advancing to their seats. However, not all passengers comply with a prescribed 1 m aisle social distance. Through agent-based simulations of passenger boarding when apron buses are used, we examine boarding policies adapted for the pandemic when the level of passenger compliance varies. To compare policies, we consider the duration of time that passengers are too close to other passengers while walking or standing in the aisle. We consider other health metrics from previous research and the time to complete boarding of the airplane. We find that the WilMA-Spread and Reverse-pyramid-Spread boarding methods provide favorable outcomes. Airlines should use WilMA-Spread if their primary concern is the risk to passengers while walking down the aisle and Reverse-pyramid-Spread if they want faster times to complete boarding of the airplane and reduced risk to aisle seat passengers from later boarding passengers. The level of the passengers' non-compliance with the prescribed aisle social distance can impact a health metric by up to 6.75%-depending on the boarding method and metric. However, non-compliance reduces the time to complete boarding of the airplane by up to 38.8% even though it increases the average time an individual passenger spends boarding.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342771 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0271544 | PLOS |
Background: Dementia presents significant challenges, including social exclusion, which can be exacerbated by public stigma. This study aimed to clarify how social distances, a common measure of public stigma, towards people living with dementia and its associated factors vary with clinical stage, presence of behavioral and psychological symptoms of dementia (BPSD), and living arrangements.
Methods: The study involved 2,589 Japanese participants aged 40 to 90 years.
Infancy
January 2025
Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.
The ability to recognize and act on others' emotions is crucial for navigating social interactions successfully and learning about the world. One way in which others' emotions are observable is through their movement kinematics. Movement information is available even at a distance or when an individual's face is not visible.
View Article and Find Full Text PDFFront Public Health
January 2025
School of Economics and Management, Anhui University of Chinese Medicine, Hefei, China.
Background: With the increasing global focus on health and the growing popularity of natural therapies, Traditional Chinese Medicine (TCM) products, including extracts, crude drugs, and herbal preparations, are widely utilized as both primary and complementary medicines worldwide. The Regional Comprehensive Economic Partnership (RCEP), spanning 15 countries across East Asia, Southeast Asia, and Oceania, offers a vast market for TCM. However, limited research has been conducted on the complex trade relations among RCEP members.
View Article and Find Full Text PDFVet Q
December 2025
College of Veterinary Medicine, Northeast Agricultural University, Harbin, China.
Foot-and-Mouth Disease is a highly contagious transboundary animal disease. FMD has caused a significant economic impact globally due to direct losses and trade restrictions on animals and animal products. This study utilized multi-distance spatial cluster analysis, kernel density analysis, directional distribution analysis to investigate the spatial distribution patterns of historical FMD epidemics.
View Article and Find Full Text PDFSci Rep
January 2025
College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, 266510, China.
The ability to assess and manage corporate credit risk enables financial institutions and investors to mitigate risk, enhance the precision of their decision-making, and adapt their strategies in a prompt and effective manner. The growing quantity of data and the increasing complexity of indicators have rendered traditional machine learning methods ineffective in enhancing the accuracy of credit risk assessment. Consequently, academics have begun to explore the potential of models based on deep learning.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!