Junya Sun

Dr. Junya Sun


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 March 2022 in Brain and Behavior
Verified
Journal Article
Open access
RSRuishan Sun
Ruishan Sun
JSJunya Sun
Junya Sun
JLJingqiang Li
Jingqiang Li
SLShuwen Li
Shuwen Li
Background: Caffeine is often used as a stimulant during fatigue, but the standard of characteristic physiological indicators of the effect of caffeine on neuromuscular fatigue has not been unified. The purpose of this systematic review and meta‐analysis is to summarize current experimental findings on the effects of caffeine on physiological indexes before and after neuromuscular fatigue, identify some characteristic neuromuscular physiological indexes to assess the potential effects of caffeine.Methods: The Preferred Reporting Items for Systematic Reviews and Meta‐analyses are followed. We systematically searched PubMed, Google academic, and Web of Science for randomized controlled trials. We searched for studies on caffeine's (i) effects on neuromuscular fatigue and (ii) the influence of physiological indexes changes. Meta‐analysis was performed for standardized mean differences (SMD) between caffeine and placebo trials in individual studies.Results: The meta‐analysis indicated that caffeine significantly improves voluntary activation (VA) (SMD = 1.46;95%CI:0.13, 2.79; p < .00001), PTw (SMD = 1.11, 95%CI: –1.61, 3.84; p < .00001), and M‐wave (SMD = 1.10, 95%CI: –0.21, 2.41; p < .00001), and a significant difference (p = .003) on measures of Peak Power (PP), and insignificant difference on measures of heart rate (HR) (I2 = 0.0, p = .84) and Maximal oxygen uptake (VO2) (I2 = 0.0, p = .76).Conclusion: The analysis showed that caffeine intake had a relatively large effect on VA, potentiated twitch (PTw), M‐wave, which can be used as characteristic indexes of caffeine's impact on neuromuscular fatigue. This conclusion tends to indicate the effects of caffeine on neuromuscular fatigue during endurance running or jumping or muscle bending and stretching. The caffeine intake had a big effect on the electromyogram (EMG) and peak power (PP), and its effect role needs to be further verified, this conclusion tends to indicate the effect of caffeine on neuromuscular fatigue during jumping or elbow bending moment movements. HR, VO2, maximal voluntary contraction (MVC) cannot be used as the characteristic indexes of caffeine on neuromuscular fatigue. This conclusion tends to indicate the effect of caffeine on neuromuscular fatigue during endurance exercise. However, the results of meta‐analysis are based on limited evidence and research scale, as well as individual differences of participants and different physical tasks, so it is necessary to interpret the results of meta‐analysis cautiously. Therefore, future research needs to explore other physiological indicators and their indicative effects in order to determine effective and accurate characteristic indicators of caffeine on neuromuscular fatigue.

1 October 2022 in BMC Public Health
Verified
Journal Article
Open access
PDF file
JSJunya Sun
Junya Sun
RSRuishan Sun
Ruishan Sun
JLJingqiang Li
Jingqiang Li
PWPing Wang
Ping Wang
NZNan Zhang
Nan Zhang
Background: In response to the COVID-19 outbreak, the Civil Aviation Administration of China (CAAC) has formulated Implementation Measures for Exemption of Crew Duty Periods and Flight Time Restrictions during the COVID-19 Outbreak. This exemption policy imposes temporary deviations from the approved crew duty periods and flight time restrictions for some transport airlines and regulates the use of multiple crews for continuous round-trip flights. However, no research has been conducted on flight crew fatigue under this exemption policy. That is, the exemption policy lacks theoretical analysis and scientific validation. Methods: Firstly, flight plans for international flights under both the exemption and the CCAR-121 Policy schemes (with three flight departure scenarios: early morning, midday and evening) are designed, and flight plans are simulated based on the SAFE model. The Karolinska Sleepiness Scale (KSS) and the PVT objective test of alertness, both of which are commonly used in the aviation industry, are then selected for use in an empirical experimental study of flight crew fatigue on two flights subject to the exemption and CCAR-121 policies. Results: The SAFE model simulation found that the fatigue risk results based on flight crews for flights departing in the early morning (4:00), at noon (12:00) and in the evening (20:00) indicate that the fatigue risk levels of flight crews operating under the exemption policy are overwhelmingly lower than or similar to those operating under the CCAR-121 policy. However, there were a few periods when the fatigue risk of crews flying under the exemption policy was higher than that of crews flying under the CCAR-121 policy, but at these times, the crews flying under both policies were either at a lower level of fatigue risk or were in the rest phase of their shifts. In the experimental study section, 40 pilots from each of the early morning (4:00), noon (12:00) and evening (20:00) departures operating under the exemption policy were selected to collect KSS scale data and PVT test data during their duty periods, and a total of 120 other pilots operating under the CCAR-121 policy were selected for the same experiment. First, the KSS scale data results found that flight pilots, whether flying under the exemption policy or under the CCAR-121 policy, had overall similar KSS scores, maintained KSS scores below the fatigue risk threshold (i.e., KSS score < 6) during the flights and that the empirical KSS data and the model simulation results from the KSS data were overall identical at the test nodes during the flight and had nearly identical trends. Finally, the results of the PVT objective test indicators showed that the overall change in 1/RT of the crews flying under the exemption policy was less than or similar to that of the crews flying under the CCAR-121 policy, while the maximum change in 1/RT of the crews under both policies was between 1 and 1.5. This indicates that the overall level of alertness of the crew flying under the exemption policy is higher than or similar to that of the crew flying under the CCAR-121 policy, while the change in alertness level of the crew before and after the mission is relatively small when flying under either policy. Conclusion: Based on the model simulation results and the results of the empirical study, it was verified that the overall fatigue risk level of flight crews operating under the exemption policy is lower than or similar to the fatigue risk level of flight crews operating under the CCAR-121 policy. Therefore, the exemption policy in response to the COVID-19 outbreak does not result in an overall increase in the level of flight crew fatigue risk compared to the original CCAR-121 policy.

11 August 2023 in Journal of Air Transport Management
Verified
Journal Article
Closed access
JSJunya Sun
Junya Sun
YLYang Liao
Yang Liao
FLFei Lu
Fei Lu
RSRui-Shan Sun
Rui-Shan Sun
HJHong-Bo Jia
Hong-Bo Jia

1 January 2023 in Ergonomics
Verified
Journal Article
Closed access
JSJunya Sun
Junya Sun
RSRuishan Sun
Ruishan Sun
Fatigue risk in humans has few biomathematical models, and existing biomathematical models have many shortcomings. We developed a biomathematical model of fatigue risk based on the concept of energy to quantify human alertness from the perspective of energy and used alertness to characterise human psychological fatigue risk. The model allows mathematical modelling of activity processes that concern sleep intensity and quality and distinguishes between intrinsic exertion in the waking state and workload exertion in the workload state. This alertness and fatigue risk biomathematical model predicts changes in human alertness and fatigue risk indices at any point in the day. We applied numerical simulation and model analysis to five cases to validate the potential value of the alertness energy fatigue risk biomathematical model. To overcome the shortcomings of current biomathematical models that evaluate fatigue risk, this study developed a biomathematical model of fatigue risk based on the concept of energy to quantify human alertness from the perspective of energy and used alertness to characterise human fatigue risk.

18 October 2022 in Frontiers in Public Health
Verified
Journal Article
Open access
JSJunya Sun
Junya Sun
SRSun Ruishan
Sun Ruishan
To predict the risk of fatigue for flight crews on international flights under the new operating model policy of the civil aviation exemption approach policy during the COVID-19 outbreak, and to provide scientific validation methods and ideas for the exemption approach policy. This paper uses the change in flight crew alertness as a validation indicator, and then constructs an alertness assessment model to predict flight crew fatigue risk based on the SAFTE model theory. Then, the corresponding in-flight rotation plans for the flight is designed according to the exemption approach policy issued by the CAAC, the CCAR-121 part policy and the real operational requirements of the airline, respectively, and finally the simulation results is compared by comparing the pilot alertness and cockpit crew alertness under the exemption approach policy and the CCAR-121 part policy with the flight duration. The results show that the flight crew alertness level for the flight in-flight rotation plan simulation designed under the exemption approach policy is higher or closer to the pilot alertness level for operational flights under the CCAR-121 Part policy. This validates the reasonableness and safety of the exemption approach policy issued by the CAAC to meet the requirements of epidemic prevention and control, and provides scientific support and solutions for fatigue monitoring and management.

4 April 2025 in Journal of Air Transport Management
Verified
Journal Article
Closed access
JSJunya Sun
Junya Sun
YLYang Liao
Yang Liao
RSRuishan Sun
Ruishan Sun
FLFei Lu
Fei Lu
YZYubin Zhou
Yubin Zhou
HJHongbo Jia
Hongbo Jia