Risk factors for neck pain in college students: a systematic review and meta-analysis (preprint)

Background: During the COVID-19 epidemic, the prevalence of neck pain among college students has increased due to the shift from offline to online learning and increasing academic and employment pressures. Therefore, this systematic review aimed to identify the personal, occupational, and psychological factors associated with the development of neck pain to promote the development of preventive strategies and early intervention treatment. Methods: Seven electronic databases were searched from inception to April 2022 for cross-sectional studies, cohort studies, case-control studies, and randomized controlled trials (RCT) on neck pain. The quality of the selected studies was assessed by American Agency for Healthcare Research and Quality (AHRQ) or the Newcastle-Ottawa scale (NOS). Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated to evaluate the effects of the included risk factors on neck pain. Results: Twenty-six studies were included, including 16,826 participants, and a total of 30 potentially associated risk factors were identified, with 20 factors only listed as risk factors in one or two studies. Ultimately, 10 risk factors were included in the meta-analysis, and all results were statistically significant (P<0.05). The factors supported by strong evidence mainly include the improper use of the pillow (OR=2.20, 95% CI: 1.39 to 3.48), lack of exercise (OR=1.88, 95% CI: 1.53 to 2.30), improper sitting posture (OR=1.97, 95% CI: 1.39 to 2.78), and history of neck and shoulder trauma (OR=2.32, 95% CI: 1.79 to 3.01), senior grade (OR=2.86, 95% CI: 2.07 to 3.95), staying up late (OR=1.80, 95% CI: 1.35 to 2.41), and long-time electronic product usage daily (OR=1.45, 95% CI: 1.27 to 1.65), long-time to bow head (OR=2.04, 95% CI: 1.58 to 2.64), emotional problems (OR=2.09; 95% CI: 1.66, 2.63). Risk factors supported by moderate evidence were high pressure (OR=1.91, 95% CI: 1.50 2.42). Conclusion: Improper use of the pillow, lack of exercise, improper sitting posture, history of neck and shoulder trauma, senior grade, staying up late, long-term electronic product usage daily, long time to bow head, high pressure, and emotional problems affect neck pain in college students. More studies have been conducted to prove the risk and relevance of the remaining 20 factors.

Cause Analysis of PM2.5 pollution during the COVID-19 lockdown in Nanning, China (preprint)

To analyze the cause of atmospheric PM2.5 pollution occurred during the COVID-19 lockdown in Nanning of Guangxi, China, Single Particulate Aerosol Mass Spectrometer, Aethalometer, Particulate Lidar, coupled with the monitoring of near-surface gaseous pollutants, meteorological conditions, remote fire spots sensing by satellite and Backward Trajectory Models were conducted during 18–24, Feb 2020. Three haze stages of pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP) were identified. The dominant source of PM2.5 in PPP was biomass burning (BB) (40.4%), followed by secondary inorganics (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganics, which contributed for 56.1% of the total PM2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in PPP was higher than those of the other two periods. The analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning city could be one of the main facotrs matters. The planetary boundary layer-relative humidity-secondary particles matter-particulate matter positive feedback mechanism was employed to elucidate the atompheric process in this study. This study highlights the importance of understanding the role of BB and meteorology in air pollution formation to call for policy for emission control strategies.

Autonomous Social Distancing in Urban Environments using a Quadruped Robot (preprint)

COVID-19 pandemic has become a global challenge faced by people all over the world. Social distancing has been proved to be an effective practice to reduce the spread of COVID-19. Against this backdrop, we propose that the surveillance robots can not only monitor but also promote social distancing. Robots can be flexibly deployed and they can take precautionary actions to remind people of practicing social distancing. In this paper, we introduce a fully autonomous surveillance robot based on a quadruped platform that can promote social distancing in complex urban environments. Specifically, to achieve autonomy, we mount multiple cameras and a 3D LiDAR on the legged robot. The robot then uses an onboard real-time social distancing detection system to track nearby pedestrian groups. Next, the robot uses a crowd-aware navigation algorithm to move freely in highly dynamic scenarios. The robot finally uses a crowd-aware routing algorithm to effectively promote social distancing by using human-friendly verbal cues to send suggestions to over-crowded pedestrians. We demonstrate and validate that our robot can be operated autonomously by conducting several experiments in various urban scenarios.