Musculoskeletal Injuries and Automation in Aerial Port Operations

2020 ◽  
Vol 91 (8) ◽  
pp. 669-673
Author(s):  
Victoria F. H. Bylsma ◽  
Bryant J. Webber ◽  
Roger A. Erich ◽  
Jameson D. Voss

INTRODUCTION: Aerial ports are being modernized with automated technologies, but the impact on musculoskeletal injury (MSKI) is unknown.METHODS: In this retrospective cohort study of U.S. Air Force aerial port technicians and traffic management technicians, we compared reported injury rates from January 2006–December 2016 and Veterans Benefits Administration disability compensation claims awarded from January 2001–March 2017. Ton-adjusted injury rates, associated lost/affected duty time, and percent risk attributable to lack of automation were compared at Dover Air Force Base (which features base-specific automation), Travis Air Force Base, Ramstein Air Base, and Yokota Air Base.RESULTS: Injuries most often occurred during aircraft/flight line activities and were typically sprains/strains, with extremities being most affected. Among aerial port technicians there were 8.0 injury reports per 1000 person-years compared to 5.2 per 1000 among traffic management technicians (incidence rate ratio = 1.5; 95% CI: 0.9, 3.0). Of the aerial port technicians with a compensation award, 70.7% included an MSKI component, whereas 75.7% of traffic management awards included an MSKI component. Aerial port technicians at Dover AFB experienced 1.4 injury reports per 1000 personnel per 1000 cargo-tons per year, lower than the other ports: 3.2 (Travis); 3.7 (Ramstein); and 7.6 (Yokota). Overall, 56% of injuries at Travis, 62% at Ramstein, and 82% at Yokota could be attributed to absence of Dover-like automation. However, mean lost/affected duty days at Dover (12.4) far exceeded those at the other bases (range: 4.5–8.6).DISCUSSION: Automating aerial ports may reduce injury rates, but the impact on lost/affected duty time requires further investigation.Bylsma VFH, Webber BJ, Erich RA, Voss JD. Musculoskeletal injuries and automation in aerial port operations. Aerosp Med Hum Perform. 2020; 91(8):669–673.

2020 ◽  
Vol 12 (22) ◽  
pp. 9662 ◽  
Author(s):  
Disheng Yi ◽  
Yusi Liu ◽  
Jiahui Qin ◽  
Jing Zhang

Exploring urban travelling hotspots has become a popular trend in geographic research in recent years. Their identification involved the idea of spatial autocorrelation and spatial clustering based on density in the previous research. However, there are some limitations to them, including the unremarkable results and the determination of various parameters. At the same time, none of them reflect the influences of their neighbors. Therefore, we used the concept of the data field and improved it with the impact of spatial interaction to solve those problems in this study. First of all, an interaction-based spatio-temporal data field identification for urban hotspots has been built. Then, the urban travelling hotspots of Beijing on weekdays and weekends are identified in six different periods. The detected hotspots are passed through qualitative and quantitative evaluations and compared with the other two methods. The results show that our method could discover more accurate hotspots than the other two methods. The spatio-temporal distributions of hotspots fit commuting activities, business activities, and nightlife activities on weekdays, and the hotspots discovered at weekends depict the entertainment activities of residents. Finally, we further discuss the spatial structures of urban hotspots in a particular period (09:00–12:00) as an example. It reflects the strong regularity of human travelling on weekdays, while human activities are more varied on weekends. Overall, this work has a certain theoretical and practical value for urban planning and traffic management.


1976 ◽  
Vol 42 (2) ◽  
pp. 467-470 ◽  
Author(s):  
T. D. Brown

There is a relationship between personality traits of enlisted personnel at one mid-west Air Force Base and their frequency of moving violations. The 52 individuals who received one or two moving violations were more emotionally stable than the 33 non-offenders and the 18 chronic offenders. Discriminant analysis showed significant differences between the personality characteristics of the occasional offender and the other two groups, but none between the chronic offender and the non-offender. The personality characteristics of the chronic offender resembled those of Zelhart's alcoholic offender and Dunbar's “accident-prone” individual. Additional research using a more heterogeneous sample might make possible identification of the high-frequency traffic violator by means of personality characteristics measured after his first offense.


2012 ◽  
Vol 32 (2) ◽  
pp. 48-56 ◽  
Author(s):  
Jonghyun Lee ◽  
Xiaoyi Liu ◽  
Peter K. Kitanidis ◽  
Ungtae Kim ◽  
Jack Parker ◽  
...  

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