The influence of night shift work and associated factors on serum uric acid in aircraft maintenance workers.

BACKGROUND AND OBJECTIVE: The prevalence of 12-hour shift work is increasing in various occupations. Shift work has been linked to circadian rhythm disruption, which may lead to hormonal changes and metabolic disorders, including alterations in glucose, lipid, and purine metabolism. Despite this, there is limited research on the potential connection between work shifts and abnormal serum uric acid (SUA) levels. Furthermore, the factors that contribute to abnormal SUA levels in shift workers are not well-understood. Therefore, this study aimed to analyze the SUA levels of shift workers employed in an aircraft maintenance company, investigate the potential association between shift work and SUA levels, and explore the factors that may influence abnormal SUA levels in shift workers. METHODS: A total of 2263 male workers from an aircraft maintenance company were included in this study using the cluster sampling method. The workers were divided into two groups based on their working shifts: night shift (N = 1047, 46.27%) and day working (N = 1216, 53.73%). A survey was conducted between April 1st and June 30th, 2022 to gather information on work, lifestyle, physical examination results, and other relevant factors. The survey included a self-designed demographic information questionnaire to collect data on workers' characteristics, medical history, years of employment, smoking and drinking habits, and main lifestyle behaviors. The workers' SUA levels were measured using uricase colorimetry. One-way ANOVA was used to compare the difference in the abnormal detection rate of SUA between the two groups, and multi-factor logistic regression analysis was used to identify the factors that influence abnormal SUA levels. RESULTS: The study indicated that 48.9% of night shift workers and 43.8% in the regular day workers had abnormal SUA levels, with a significant difference between the two groups (χ2 = 6.125, P = 0.013). Factors such as circadian rhythm type, shift work, age, the taste of diet, type of diet, smoking, overweight or obesity based on body mass index (BMI), concentration of urine creatinine (CREA), total cholesterol, triglyceride, and low-density lipoprotein cholesterol were found to be correlated with SUA abnormalities (P < 0.05). The risk of developing SUA abnormalities was found to be higher in individuals with an intermittent (OR = 1.34, 95% CI: 0.83-2.12, P < 0.05) or evening circadian rhythm type (OR = 1.45, 95% CI: 0.86-2.43, P > 0.05) compared to those with a morning type. Additionally, factors such as night shift work, a high-sodium diet, smoking, a diet high in meat and low in vegetables, being overweight or obese, and higher levels of CREA were also found to increase the risk of developing SUA abnormalities. The study also revealed a significant dose-response relationship between BMI and abnormal uric acid levels. After controlling for other factors, the risk of developing SUA abnormalities was found to be 1.18 times higher in the night shift work group than in the day work group (OR = 1.18, 95% CI:1.02-1.34, P = 0.01). CONCLUSION: Shift work has been linked to a higher risk of developing SUA abnormalities, and there are several factors that may contribute to this risk. To prevent diseases, it is recommended that enterprises implement better health monitoring and management practices for shift workers.

Aerial Wildlife Image Repository for animal monitoring with drones in the age of artificial intelligence.

Drones (unoccupied aircraft systems) have become effective tools for wildlife monitoring and conservation. Automated animal detection and classification using artificial intelligence (AI) can substantially reduce logistical and financial costs and improve drone surveys. However, the lack of annotated animal imagery for training AI is a critical bottleneck in achieving accurate performance of AI algorithms compared to other fields. To bridge this gap for drone imagery and help advance and standardize automated animal classification, we have created the Aerial Wildlife Image Repository (AWIR), which is a dynamic, interactive database with annotated images captured from drone platforms using visible and thermal cameras. The AWIR provides the first open-access repository for users to upload, annotate, and curate images of animals acquired from drones. The AWIR also provides annotated imagery and benchmark datasets that users can download to train AI algorithms to automatically detect and classify animals, and compare algorithm performance. The AWIR contains 6587 animal objects in 1325 visible and thermal drone images of predominantly large birds and mammals of 13 species in open areas of North America. As contributors increase the taxonomic and geographic diversity of available images, the AWIR will open future avenues for AI research to improve animal surveys using drones for conservation applications. Database URL: https://projectportal.gri.msstate.edu/awir/.

Aircraft turnaround time dynamic prediction based on Time Transition Petri Net.

Accurate aircraft turnaround time prediction is an important way to coordinate the operation time of airport ground service and improve the efficiency of airport operation. In this paper, by analyzing the aircraft turnaround operation process, a description model based on Time Transition Petri Net is proposed. The model describes the flight turnaround operation process and the logical relationship of the operation. According to the model, a dynamic prediction method of turnaround time based on Bayesian theorem is designed. According to the actual landing time of the flight, the aircraft turnaround time is predicted. The specific method is to obtain the prior probability distribution and joint distribution law of each operation link according to the flight history data, and use Shapiro-Wilke to test the prior probability distribution of each link. Based on the analysis and comparison between the actual turnaround data of a large airport in China and the forecast data proposed in this paper, the root-mean-square error 3.75 minutes and the mean absolute error 3.40 minutes can be calculated. This paper contributes to the improvement of flight punctuality rate and airport clearance level.

A New Methodology for High Spatiotemporal Resolution Measurements of Air Volatile Organic Compounds: From Sampling to Data Deconvolution.

Monitoring of volatile organic compounds (VOCs) in air is crucial for understanding their atmospheric impacts and advancing their emission reduction plans. This study presents an innovative integrated methodology suitable for achieving semireal-time high spatiotemporal resolution three-dimensional measurements of VOCs from ground to hundreds of meters above ground. The methodology integrates an active AirCore sampler, custom-designed for deployment from unmanned aerial vehicles (UAV), a proton-transfer-reaction mass spectrometry (PTR-MS) for sample analysis, and a data deconvolution algorithm for improved time resolution for measurements of multiple VOCs in air. The application of the deconvolution technique significantly improves the signal strength of data from PTR-MS analysis of AirCore samples and enhances their temporal resolution by 4 to 8 times to 4-11 s. A case study demonstrates that the methodology can achieve sample collection and analysis of VOCs within 45 min, resulting in >120-360 spatially resolved data points for each VOC measured and achieving a horizontal resolution of 20-55 m at a UAV flight speed of 5 m/s and a vertical resolution of 5 m. This methodology presents new possibilities for acquiring 3-dimensional spatial distributions of VOC concentrations, effectively tackling the longstanding challenge of characterizing three-dimensional VOC distributions in the lowest portion of the atmospheric boundary layer.

Effects of a mat Pilates-based exercise program for low back pain in helicopter pilots of the Brazilian Air Force: Randomized controlled trial.

INTRODUCTION: Helicopter pilots may present chronic low back pain due to vibration exposure and asymmetric posture during flight. OBJECTIVES: To analyze the effects of a Pilates-based exercise program on low back pain of helicopter pilots of the Brazilian Air Force. METHODS: This is a randomized controlled trial with fifteen helicopter pilots of the Brazilian Air Force, who were assessed for pain intensity (Numerical Pain Rating Scale), disability associated with low back pain, and spine muscle endurance in three positions: trunk extension (Ito test) and left and right lateral bridge. Individuals were randomly distributed into the regular exercises group (REG) (n = 7), oriented to maintain their exercise routine, and Pilates group (PG) (n = 8), which performed an exercise program based on Pilates method twice a week for 12 weeks. Reassessments occurred after 6 and 12 weeks. Data were analyzed on SPSS 20.0 software using a significance level of 5%. RESULTS: PG showed a significant reduction in low back pain after 12 weeks of training compared with REG (mean difference of 3.5 points, p < 0.0001). We also observed increased endurance of trunk extensors (p = 0.002) and right (p = 0.001) and left lateral muscles (p = 0.001) in the PG compared with REG. However, the indexes of disability did not change between groups. CONCLUSION: Pain intensity was significantly reduced while spine muscle endurance increased in PG compared with REG after intervention; thus, Pilates-based exercises should be considered in physical conditioning programs for helicopter pilots.

The Risk of Aircraft-Acquired SARS-CoV-2 Transmission during Commercial Flights: A Systematic Review.

The aircraft-acquired transmission of SARS-CoV-2 poses a public health risk. Following PRISMA guidelines, we conducted a systematic review and analysis of articles, published prior to vaccines being available, from 24 January 2020 to 20 April 2021 to identify factors important for transmission. Articles were included if they mentioned index cases and identifiable flight duration, and excluded if they discussed non-commercial aircraft, airflow or transmission models, cases without flight data, or that were unable to determine in-flight transmission. From the 15 articles selected for in-depth review, 50 total flights were analyzed by flight duration both as a categorical variable-short (<3 h), medium (3-6 h), or long flights (>6 h)-and as a continuous variable with case counts modeled by negative binomial regression. Compared to short flights without masking, medium and long flights without masking were associated with 4.66-fold increase (95% CI: [1.01, 21.52]; p < 0.0001) and 25.93-fold increase in incidence rates (95% CI: [4.1, 164]; p < 0.0001), respectively; long flights with enforced masking had no transmission reported. A 1 h increase in flight duration was associated with 1.53-fold (95% CI: [1.19, 1.66]; p < 0.001) increase in the incidence rate ratio (IRR) of cases. Masking should be considered for long flights.

Advancing noise management in aviation: Strategic approaches for preventing noise-induced hearing loss.

As urbanization and population growth escalate, the challenge of noise pollution intensifies, particularly within the aviation industry. This review examines current insights into noise-induced hearing loss (NIHL) in aviation, highlighting the risks to pilots, cabin crew, aircraft maintenance engineers, and ground staff from continuous exposure to high-level noise. It evaluates existing noise management and hearing conservation strategies, identifying key obstacles and exploring new technological solutions. While progress in developing protective devices and noise control technologies is evident, gaps in their widespread implementation persist. The study underscores the need for an integrated strategy combining regulatory compliance, technological advances, and targeted educational efforts. It advocates for global collaboration and policy development to safeguard the auditory health of aviation workers and proposes a strategic framework to enhance hearing conservation practices within the unique challenges of the aviation sector.

Impacts of Fuel Stage Ratio on the Morphological and Nanostructural Characteristics of Soot Emissions from a Twin Annular Premixing Swirler Combustor.

Soot particles emitted from aircraft engines constitute a major anthropogenic source of pollution in the vicinity of airports and at cruising altitudes. This emission poses a significant threat to human health and may alter the global climate. Understanding the characteristics of soot particles, particularly those generated from Twin Annular Premixing Swirler (TAPS) combustors, a mainstream combustor in civil aviation engines, is crucial for aviation environmental protection. In this study, a comprehensive characterization of soot particles emitted from TAPS combustors was conducted using scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), and Raman spectroscopy. The morphology and nanostructure of soot particles were examined across three distinct fuel stage ratios (FSR), at 10%, 15%, and 20%. The SEM analysis of soot particle morphology revealed that coated particles constitute over 90% of the total particle sample, with coating content increasing proportionally to the fuel stage ratio. The results obtained from HRTEM indicated that average primary particle sizes increase with the fuel stage ratio. The results of HRTEM and Raman spectroscopy suggest that the nanostructure of soot particles becomes more ordered and graphitized with an increasing fuel stage ratio, resulting in lower oxidation activity. Specifically, soot fringe length increased with the fuel stage ratio, while soot fringe tortuosity and separation distance decreased. In addition, there is a prevalent occurrence of defects in the graphitic lattice structure of soot particles, suggesting a high degree of elemental carbon disorder.

Frequency-dependent tolerance to aircraft disturbance drastically alters predicted impact on shorebirds.

Anthropogenic disturbance of wildlife is increasing globally. Generalizing impacts of disturbance to novel situations is challenging, as the tolerance of animals to human activities varies with disturbance frequency (e.g. due to habituation). Few studies have quantified frequency-dependent tolerance, let alone determined how it affects predictions of disturbance impacts when these are extrapolated over large areas. In a comparative study across a gradient of air traffic intensities, we show that birds nearly always fled (80%) if aircraft were rare, while birds rarely responded (7%) if traffic was frequent. When extrapolating site-specific responses to an entire region, accounting for frequency-dependent tolerance dramatically alters the predicted costs of disturbance: the disturbance map homogenizes with fewer hotspots. Quantifying frequency-dependent tolerance has proven challenging, but we propose that (i) ignoring it causes extrapolations of disturbance impacts from single sites to be unreliable, and (ii) it can reconcile published idiosyncratic species- or source-specific disturbance responses.

Characterizing and Predicting nvPM Size Distributions for Aviation Emission Inventories and Environmental Impact.

Concerns about civil aviation's air quality and environmental impacts have led to recent regulations on nonvolatile particulate matter (nvPM) mass and number emissions. Although these regulations do not mandate measuring particle size distribution (PSD), understanding PSDs is vital for assessing the environmental impacts of aviation nvPM. This study introduces a comprehensive data set detailing PSD characteristics of 42 engines across 19 turbofan types, ranging from unregulated small business jets to regulated large commercial aircraft. Emission tests were independently performed by using the European and Swiss reference nvPM sampling and measurement systems with parallel PSD measurements. The geometric mean diameter (GMD) at the engine exit strongly correlated with the nvPM number-to-mass ratio (N/M) and thrust, varying from 7 to 52 nm. The engine-exit geometric standard deviation ranged from 1.7 to 2.5 (mean of 2.05). The study proposes empirical correlations to predict GMD from N/M data of emissions-certified engines. These predictions are expected to be effective for conventional rich-burn engines and might be extended to novel combustor technologies if additional data become available. The findings support the refinement of emission models and help in assessing the aviation non-CO2 climate and air quality impacts.

Long-term exposure to transportation noise and diabetes mellitus mortality: a national cohort study and updated meta-analysis.

BACKGROUND: Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort. METHODS: During 15 years of follow-up (2001-2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined). RESULTS: HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively). CONCLUSIONS: This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

The Impact of Various Cockpit Display Interfaces on Novice Pilots' Mental Workload and Situational Awareness: A Comparative Study.

Future airspace is expected to become more congested with additional in-service cargo and commercial flights. Pilots will face additional burdens in such an environment, given the increasing number of factors that they must simultaneously consider while completing their work activities. Therefore, care and attention must be paid to the mental workload (MWL) experienced by operating pilots. If left unaddressed, a state of mental overload could affect the pilot's ability to complete his or her work activities in a safe and correct manner. This study examines the impact of two different cockpit display interfaces (CDIs), the Steam Gauge panel and the G1000 Glass panel, on novice pilots' MWL and situational awareness (SA) in a flight simulator-based setting. A combination of objective (EEG and HRV) and subjective (NASA-TLX) assessments is used to assess novice pilots' cognitive states during this study. Our results indicate that the gauge design of the CDI affects novice pilots' SA and MWL, with the G1000 Glass panel being more effective in reducing the MWL and improving SA compared with the Steam Gauge panel. The results of this study have implications for the design of future flight deck interfaces and the training of future pilots.

Measurement of the vertical distributions of atmospheric pollutants using an uncrewed aerial vehicle platform in Xi'an, China.

Vertical observations of atmospheric pollutants play crucial roles in a comprehensive understanding of the distribution characteristics and transport of atmospheric pollutants. A hexacopter uncrewed aerial vehicle equipped with miniature monitors was employed to measure the vertical distribution of atmospheric pollutants within a height of 1000 m at a rural site in Xi'an, China, in 2021. The concentrations of carbon monoxide (CO) and particulate matter (PM) showed generally decreasing trends with increasing height. The ozone (O3) concentration showed a general increasing trend with height followed by a gradual decreasing trend. Vertical decrements of PM2.5 and CO from 0 to 1000 m were significantly (p < 0.05) lower on observation days during summer (14.0 ± 8.1 µg m-3 and 8.7 ± 6.6 ppb, respectively), compared with those in winter (78.3 ± 14.1 µg m-3 and 34.8 ± 17.3 ppb, respectively). The horizontal transport of PM and CO mostly occurred in the morning and at night during winter observations at an altitude of 400-500 m. During the winter haze, the PM and CO profile concentrations below 500 m increased substantially with the decrease in the height of the thermal inversion layer. Vertical O3 transportation was observed in the afternoon and evening during summer, and a ∼37.7% (11.6 ppb) increase in ground-level O3 was observed in relation to vertical transport from the upper atmosphere. The results provide insights into the vertical distribution and transport of atmospheric pollutants in rural areas near cities.

Usefulness of aircraft and airport wastewater for monitoring multiple pathogens including SARS-CoV-2 variants.

BACKGROUND: As global travel resumed in coronavirus disease 2019 (COVID-19) endemicity, the potential of aircraft wastewater monitoring to provide early warning of disease trends for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and other infectious diseases, particularly at international air travel hubs, was recognized. We therefore assessed and compared the feasibility of testing wastewater from inbound aircraft and airport terminals for 18 pathogens including SARS-CoV-2 in Singapore, a popular travel hub in Asia. METHODS: Wastewater samples collected from inbound medium- and long-haul flights and airport terminals were tested for SARS-CoV-2. Next Generation Sequencing was carried out on positive samples to identify SARS-CoV-2 variants. Airport and aircraft samples were further tested for 17 other pathogens through quantitative reverse transcription polymerase chain reaction. RESULTS: The proportion of SARS-CoV-2-positive samples and the average virus load was higher for wastewater samples from aircraft as compared with airport terminals. Cross-correlation analyses indicated that viral load trends from airport wastewater led local COVID-19 case trends by 2-5 days. A total of 10 variants (44 sub-lineages) were successfully identified from aircraft wastewater and airport terminals, and four variants of interest and one variant under monitoring were detected in aircraft and airport wastewater 18-31 days prior to detection in local clinical cases. The detection of five respiratory and four enteric viruses in aircraft wastewater samples further underscores the potential to expand aircraft wastewater to monitoring pathogens beyond SARS-CoV-2. CONCLUSION: Our findings demonstrate the feasibility of aircraft wastewater testing for monitoring infectious diseases threats, potentially detecting signals before clinical cases are reported. The triangulation of similar datapoints from aircraft wastewater of international travel nodes could therefore serve as a useful early warning system for global health threats.

Worldwide Regulation of the Medical Emergency Kit and First Aid Kit.

INTRODUCTION: On-board medical emergencies are increasing. Different geographies have different legislation and requirements for medical emergency kits and first aid kits. A comprehensive review to compare the contents of both kits was conducted, including the International Air Transport Association, European Union Aviation Safety Agency, and Federal Aviation Administration, as well as some from other geographical areas of the globe to cover continents and regions with the highest air traffic, such as Brazil, Kenya, Australia, and Taiwan.METHODS: On June 10, 2023, a search was conducted using standardized medical terms (medical subject headings) within the PubMed® database. The relevant terms identified were "Aircraft" and "Medical Emergencies"; articles published within the last 10 yr were filtered. Subsequently, even articles published before 2013 were consulted if cited by the initial ones. The main regulatory entities' documentation was found using the Google search engine and consulted.CONCLUSIONS: It is impossible to be prepared for every emergency on board. Still, as doctors, we have a moral and ethical obligation to try to improve the outcomes of those emergencies. Getting a standardized report of every on-board emergency is crucial. That would make optimizing the items to include in the emergency and first aid kits easier. There are many similarities among the compared entities, but essential differences have been found. There is room for improvement, especially for pediatric travelers.Oliveira ATB. Worldwide regulation of the medical emergency kit and first aid kit. Aerosp Med Hum Perform. 2024; 95(6):321-326.

Rapid assessment of cosmic radiation exposure in aviation based on BP neural network method.

Cosmic radiation exposure is one of the important health concerns for aircrews. In this work, we constructed a back propagation neural network model for the real-time and rapid assessment of cosmic radiation exposure to the public in aviation. The multi-dimensional dataset for this neural network was created from modeling the process of cosmic ray transportation in magnetic field by geomagnetic cutoff rigidity method and air shower simulation by a Monte Carlo based Geant4 code. The dataset was characterized by parameters including cosmic ray energy spectrum, Kp-index, coordinated universal time, altitude, latitude, and longitude. The effective dose and dose rate was finally converted from the particle fluxes at flight position by the neural network. This work shows a good agreement with other models from International Civil Aviation Organization. It is also illustrated that the effective dose rate by galactic cosmic ray is <10 µSv h-1 and the value during ground level enhancement (GLE) 42 is 4 ~ 10 times larger on the routes calculated in this work. In GLE 69, the effective dose rate reaches several mSv h-1 in the polar region. Based on this model, a real-time warning system is achieved.

Parameterization of H2SO4 and organic contributions to volatile PM in aircraft plumes at ground idle.

Volatile Particulate Matter (vPM) emissions are challenging to measure and quantify, since they are not present in the condensed form at the engine exit plane and they evolve to first form in the aircraft plume and then continue to grow and change as they mix and dilute in the ambient atmosphere. To better understand the issues associated with the initial formation and growth of vPM, a modeling study has been undertaken to examine several key parameters that affect the formation and properties of the vPM that is created in the initial cooling and dilution of the aircraft exhaust. A modeling tool (Aerosol Dynamic Simulation Code, ADSC) that was developed and enhanced over a series of past research projects supported by NASA, DoD's SERDP/ESTCP, and FAA was used to perform a parametric analysis of vPM. The parameters of fuel sulfur content (FSC), emitted condensable hydrocarbon (HC) concentrations, and the species profile of the HCs were used to construct a computational matrix that framed a wide range of expected parameter values. This computational matrix was executed for two representative commercial aircraft engines at ground idle and results were obtained for distances of 250 m and 1000 m downstream. From prior results, the most significant vPM emissions occur at the lowest power settings, so an engine power condition of 7% rated thrust was used. A primary goal of the parametric study is to develop an updated vPM modeling methodology and also to help interpret data collected in experimental campaigns. The parameterization proposed here allows the vPM emission composition and particle numbers to be estimated in greater detail than current methods. The aim is to provide additional understanding on how the vPM properties vary with fuel and engine parameters to increase the utility of vPM predictions.Implications: Volatile Particulate Matter (vPM) is an important contribution to the total PM emitted by aviation engines. While vPM is not currently a part of engine emissions certification regulations, vPM is used in aviation environmental impact assessments and for air quality modeling in and around airports. Current methods in use, such as FOA, were developed before many recent advances in experimental data acquisition and in understanding of vPM processes. The parameterization proposed here allows the vPM emission composition and particle numbers to be estimated in greater detail than current methods. These estimates can be used to develop inventories and provide a better estimate of total emission for most aviation engines. Its use in international regulatory tools can inform possible future regulatory actions regarding vPM.