Visual function correlates of self-reported vision-related nighttime driving difficulties / La función visual se correlaciona con las dificultades de conducción nocturna relacionadas con la visión autoinformadas

Purpose: To investigate the visual function correlates of self-reported vision-related night driving difficulties among drivers. Methods: One hundred and seven drivers (age: 46.06 ± 8.24, visual acuity [VA] of 0.2logMAR or better) were included in the study. A standard vision and night driving questionnaire (VND-Q) was administered. VA and contrast sensitivity were measured under photopic and mesopic conditions. Mesopic VA was remeasured after introducing a peripheral glare source into the participants' field of view to enable computation of disability glare index. Regression analyses were used to assess the associations between VND-Q scores, and visual function measures. Results: The mean VND-Q score was -3.96±1.95 logit (interval scale score: 2.46±1.28). Simple linear regression models for photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index significantly predicted VND-Q score (P<0.05), with mesopic VA and disability glare index accounting for the greatest variation (21 %) in VND-Q scores followed by photopic contrast sensitivity (19 %), and mesopic contrast sensitivity (15 %). A multiple regression model to determine the association between the predictors (photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index) and VND-Q score yielded significant results, F (4, 102) = 8.58, P < 0.001, adj. R2 = 0.2224. Seeing dark-colored cars was the most challenging vision task. Conclusion: Changes in mesopic visual acuity, photopic and mesopic contrast sensitivity, as well as disability glare index are associated with and explain night driving-related visual difficulties. It is recommended to incorporate measurement of these visual functions into assessments related to driving performance.(AU)

Identifying interactions among factors related to death occurred at the scene of traffic accidents: Application of "logic regression" method.

Aim: Traffic accidents are caused by several interacting risk factors. This study aimed to investigate the interactions among risk factors associated with death at the accident scene (DATAS) as an indicator of the crash severity, for pedestrians, passengers, and drivers by adopting "Logic Regression" as a novel approach in the traffic field. Method: A case-control study was designed based on the police data from the Road Traffic Injury Registry in northwest of Iran during 2014-2016. For each of the pedestrians, passengers, and drivers' datasets, logic regression with "logit" link function was fitted and interactions were identified using Annealing algorithm. Model selection was performed using the cross-validation and the null model randomization procedure. Results: regarding pedestrians, "The occurrence of the accident outside a city in a situation where there was insufficient light" (OR = 6.87, P-value<0.001) and "the age over 65 years" (OR = 2.97, P-value<0.001) increased the chance of DATAS. "Accidents happening in residential inner-city areas with a light vehicle, and presence of the pedestrians in the safe zone or on the non-separate two-way road" combination lowered the chance of DATAS (OR = 0.14, P-value<0.001). For passengers, "Accidents happening in outside the city or overturn of the vehicle" combination (OR = 8.55, P-value<0.001), and "accidents happening on defective roads" (OR = 2.18, P-value<0.001) increased the odds of DATAS; When "driver was not injured or the vehicle was two-wheeled", chance of DATAS decreased for passengers (OR = 0.25, p-value<0.001). The odds of DATAS were higher for "drivers who had a head-on accident, or drove a two-wheeler vehicle, or overturned the vehicle" (OR = 4.03, P-value<0.001). "Accident on the roads other than runway or the absence of a multi-car accident or an accident in a non-residential area" (OR = 6.04, P-value<0.001), as well "the accident which occurred outside the city or on defective roads, and the drivers were male" had a higher risk of DATAS for drivers (OR = 5.40, P-value<0.001). Conclusion: By focusing on identifying interaction effects among risk factors associated with DATAS through logic regression, this study contributes to the understanding of the complex nature of traffic accidents and the potential for reducing their occurrence rate or severity. According to the results, the simultaneous presence of some risk factors such as the quality of roads, skill of drivers, physical ability of pedestrians, and compliance with traffic rules play an important role in the severity of the accident. The revealed interactions have practical significance and can play a significant role in the problem-solving process and facilitate breaking the chain of combinations among the risk factors. Therefore, practical suggestions of this study are to control at least one of the risk factors present in each of the identified combinations in order to break the combination to reduce the severity of accidents. This may have, in turn, help the policy-makers, road users, and healthcare professionals to promote road safety through prioritizing interventions focusing on effect size of simultaneous coexistence of crash severity determinants and not just the main effects of single risk factors or their simple two-way interactions.

A lightweight network architecture for traffic sign recognition based on enhanced LeNet-5 network.

As an important part of the unmanned driving system, the detection and recognition of traffic sign need to have the characteristics of excellent recognition accuracy, fast execution speed and easy deployment. Researchers have applied the techniques of machine learning, deep learning and image processing to traffic sign recognition successfully. Considering the hardware conditions of the terminal equipment in the unmanned driving system, in this research work, the goal was to achieve a convolutional neural network (CNN) architecture that is lightweight and easily implemented for an embedded application and with excellent recognition accuracy and execution speed. As a classical CNN architecture, LeNet-5 network model was chosen to be improved, including image preprocessing, improving spatial pool convolutional neural network, optimizing neurons, optimizing activation function, etc. The test experiment of the improved network architecture was carried out on German Traffic Sign Recognition Benchmark (GTSRB) database. The experimental results show that the improved network architecture can obtain higher recognition accuracy in a short interference time, and the algorithm loss is significantly reduced with the progress of training. At the same time, compared with other lightweight network models, this network architecture gives a good recognition result, with a recognition accuracy of 97.53%. The network structure is simple, the algorithm complexity is low, and it is suitable for all kinds of terminal equipment, which can have a wider application in unmanned driving system.

Road traffic noise exposure and its impact on health: evidence from animal and human studies-chronic stress, inflammation, and oxidative stress as key components of the complex downstream pathway underlying noise-induced non-auditory health effects.

In heavily urbanized world saturated with environmental pollutants, road traffic noise stands out as a significant factor contributing to widespread public health issues. It contributes in the development of a diverse range of non-communicable diseases, such as cardiovascular diseases, metabolic dysregulation, cognitive impairment, and neurodegenerative disorders. Although the exact mechanisms behind these non-auditory health effects remain unclear, the noise reaction model centres on the stress response to noise. When exposed to noise, the body activates the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system, leading to the secretion of stress hormones like catecholamines and cortisol. Prolonged exposure to noise-induced stress results in chronic inflammation and oxidative stress. This review underscores the role of inflammation and oxidative stress in the progression of noise-induced vascular dysfunction, disruption of the circadian rhythm, accelerated aging, neuroinflammation, and changes in microbiome. Additionally, our focus is on understanding the interconnected nature of these health outcomes: These interconnected factors create a cascade effect, contributing to the accumulation of multiple risk factors that ultimately lead to severe adverse health effects.

Application of soil magnetometry and geochemical methods to investigate soil contamination with antimony.

The aim of the study was an assessment of the pollution level and identification of the antimony sources in soils in areas subjected to industrial anthropopressure from: transport, metallurgy and electrical waste recycling. The combination of soil magnetometry, chemical analyzes using atomic spectrometry (ICP-OES and ICP-MS), Sb fractionation analysis, statistical analysis (Pearson's correlation matrix, factor analysis) as well as Geoaccumulation Index, Pollution Load Index, and Sb/As factor allowed not only the assessment of soil contamination degree, but also comprehensive identification of different Sb sources. The results indicate that the soil in the vicinity of the studied objects was characterized by high values of magnetic susceptibility and thus, high contents of potentially toxic elements. The most polluted area was in the vicinity of electrical waste processing plants. Research has shown that the impact of road traffic and wearing off brake blocks, i.e. traffic anthropopression in general, has little effect on the surrounding soil in terms of antimony content. Large amounts of Pb, Zn, As and Cd were found in the soil collected in the vicinity of the heap after the processing of zinc-lead ores, the average antimony (11.31 mg kg-1) content was lower in the vicinity of the heap than in the area around the electrical and electronic waste processing plant, but still very high. Antimony in the studied soils was demobilized and associated mainly with the residual fraction.

Forensic Assessment of Alcohol Intoxication in Cases of Fatal Road Traffic Accidents in Lithuania.

Background: There is strong evidence that alcohol consumption is a significant risk factor for fatal road traffic accidents. It is estimated that the number of alcohol-related road accidents remains high in the past few years in Lithuania. This study aims to examine the prevalence of alcohol in blood samples collected from the autopsy results of road traffic accident victims. Materials and methods: A retrospective study of 136 road traffic accident victims was performed in State Forensic Medicine Service of Lithuania in the period of 2013 to 2023. We analyzed blood alcohol concentration (BAC) in relation to sex, age, road user type, place and time of the day at death. Results: 31% of the victims were under influence of alcohol at the time of death, with mean BAC 1.99 ± 0.92‰. The mean BAC was 2.16 ± 0.8‰ in male and 1.18 ± 1.12‰ in female group. By the type of road users, 23% of the pedestrians (mean BAC 2.45 ± 0.71‰), 32% of car drivers (mean BAC 2.13 ± 0.75‰), 41% of vehicle passengers (mean BAC of 1.73 ± 1.19‰), 37% of the motorcycle riders (mean BAC of 1.28 ± 0.53‰), 37% of the cyclists (mean BAC of 1.15 ± 0.75‰) were found to be intoxicated during the time of accident. Highest mean blood alcohol concentration was found during the night time hours (9 p. m. - 5 a. m.) 2.28 ± 0.91, comparing to in afternoon hours (12 p. m. - 5 p. m.) 1.49 ± 0.99, evening hours (5 p. m. - 9 p. m.) 2.10 ± 0.73 and morning hours (5 a. m. - 12 p. m.) 1.94 ± 1.00. The mean BAC in road traffic accidents during summer was 1.48 ± 0.71‰, spring 2.25 ± 0.76‰, autumn 2.12 ± 1‰, winter 2.42 ± 1‰. Conclusions: Alcohol consumption by road users is a significant contributing factor in road traffic accidents and their outcomes in Lithuania.

Evaluating the quality of sediments in streams draining contrasting land-use areas in Osogbo metropolis, southwestern Nigeria.

The attendant effects of urbanization on the environment and human health are evaluable by measuring the potentially harmful element (PHE) concentrations in environmental media such as stream sediments. To evaluate the effect of urbanization in Osogbo Metropolis, the quality of stream sediments from a densely-populated area with commercial/industrial activities was contrasted with sediments from a sparsely-populated area with minimal anthropogenic input.Forty samples were obtained: 29 from Okoko stream draining a Residential/Commercial Area (RCA, n = 14) and an Industrial Area (IA, n = 15), and 11 from Omu stream draining a sparsely-populated area (SPA). The samples were air-dried, sieved to < 75 micron fraction, and analysed for PHEs using inductively-coupled plasma atomic emission spectrometry (ICP-AES). Index of geoaccumulation (Igeo), pollution index (PI), ecological risk factor (Er) and index (ERI) were used for assessment. Inter-elemental relationships and source identification were done using Pearson's correlation matrix and principal component analysis (PCA).PHE concentrations in the stream sediments were RCA: Zn > Pb > Cu > Cr > Sr > Ni > Co, IA: Zn > Cr > Ni > Co > Pb > Cu > Sr and SPA: Zn > Co > Cr > Cu > Sr > Ni > Pb. Igeo calculations revealed moderate-heavy contamination of Cu, Pb and Zn in parts of RCA, moderate-heavy contamination of Zn in IA while SPA had moderate contamination of Co and Zn. PI values revealed that stream sediments of RCA are extremely polluted, while those of IA and SPA are moderately and slightly polluted, respectively.The pollution of the stream sediments in RCA and IA is adduced to anthropogenic activities like vehicular traffic, automobile repairs/painting, blacksmithing/welding and metal scraping. In SPA however, the contamination resulted from the application of herbicides/fertilizers for agricultural purposes.

Road hazard: a systematic review of traffic injuries following recreational cannabis legalization.

PURPOSE: Acute cannabis use is associated with impaired driving performance and increased risk of motor vehicle crashes. Following the Canadian Cannabis Act's implementation, it is essential to understand how recreational cannabis legalization impacts traffic injuries, with a particular emphasis on Canadian emergency departments. This study aims to assess the impact of recreational cannabis legalization on traffic-related emergency department visits and hospitalizations in the broader context of North America. METHODS: A systematic review was conducted according to best practices and reported using PRISMA 2020 guidelines. The protocol was registered on July 5, 2022 (PROSPERO CRD42022342126). MEDLINE(R) ALL (OvidSP), Embase (OvidSP), CINAHL (EBSCOHost), and Scopus were searched without language or date restrictions up to October 12, 2023. Studies were included if they examined cannabis-related traffic-injury emergency department visits and hospitalizations before and after recreational cannabis legalization. The risk of bias was assessed. Meta-analysis was not possible due to heterogeneity. RESULTS: Seven studies were eligible for the analysis. All studies were conducted between 2019 and 2023 in Canada and the United States. We found mixed results regarding the impact of recreational cannabis legalization on emergency department visits for traffic injuries. Four of the studies included reported increases in traffic injuries after legalization, while the remaining three studies found no significant change. There was a moderate overall risk of bias among the studies included. CONCLUSIONS: This systematic review highlights the complexity of assessing the impact of recreational cannabis legalization on traffic injuries. Our findings show a varied impact on emergency department visits and hospitalizations across North America. This underlines the importance of Canadian emergency physicians staying informed about regional cannabis policies. Training on identifying and treating cannabis-related impairments should be incorporated into standard protocols to enhance response effectiveness and patient safety in light of evolving cannabis legislation.

RéSUMé: OBJECTIF: La consommation aiguë de cannabis est associée à une conduite avec facultés affaiblies et à un risque accru d'accidents de la route. À la suite de la mise en œuvre de la Loi canadienne sur le cannabis, il est essentiel de comprendre l'incidence de la légalisation du cannabis à des fins récréatives sur les blessures de la route, en mettant l'accent sur les services d'urgence canadiens. Cette étude vise à évaluer l'impact de la légalisation du cannabis à des fins récréatives sur les visites et les hospitalisations aux urgences liées à la circulation dans le contexte plus large de l'Amérique du Nord. MéTHODES: Une revue systématique a été menée selon les meilleures pratiques et a été rapportée en utilisant les directives PRISMA 2020. Le protocole a été enregistré le 5 juillet 2022 (PROSPERO CRD42022342126). MEDLINE(R) ALL (OvidSP), Embase (OvidSP), CINAHL (EBSCOHost) et Scopus ont été fouillés sans restriction de langue ou de date jusqu'au 12 octobre 2023. Des études ont été incluses si elles examinaient les visites aux urgences et les hospitalisations avant et après la légalisation du cannabis à des fins récréatives. Le risque de biais a été évalué. La méta-analyse n'était pas possible en raison de l'hétérogénéité. RéSULTATS: Sept études étaient admissibles à l'analyse. Toutes les études ont été menées entre 2019 et 2023 au Canada et aux États-Unis. Nous avons trouvé des résultats mitigés concernant l'impact de la légalisation du cannabis récréatif sur les visites aux urgences pour les blessures de la route. Quatre des études incluaient une augmentation des accidents de la route après la légalisation, tandis que les trois autres études n'ont révélé aucun changement significatif. Le risque global de biais était modéré parmi les études incluses. CONCLUSIONS: Cet examen systématique met en évidence la complexité de l'évaluation de l'impact de la légalisation du cannabis récréatif sur les blessures de la route. Nos résultats montrent un impact varié sur les visites aux urgences et les hospitalisations en Amérique du Nord. Cela souligne l'importance pour les médecins d'urgence canadiens de se tenir informés des politiques régionales sur le cannabis. La formation sur l'identification et le traitement des déficiences liées au cannabis devrait être intégrée aux protocoles normalisés afin d'améliorer l'efficacité de l'intervention et la sécurité des patients à la lumière de l'évolution de la législation sur le cannabis.

p­Phenylenediamine antioxidants in PM2.5: New markers for traffic in positive matrix factorization source apportionment.

The extensive utilization of rubber-related products can lead to a substantial release of p-phenylenediamine (PPD) antioxidants into the environment. In recent years, studies mainly focus on the pollution characteristics and health risks of PM2.5-bound PPDs. This study presents long-time scale data of PPDs and N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q) in PM2.5 and proposes the innovative use of PPDs as new markers for vehicular emissions in the Positive Matrix Factorization (PMF) source apportionment. The results indicate that PPDs and 6PPD-Q were detectable in 100 % of the winter PM2.5 samples, and the concentration ranges of PPDs and 6PPD-Q are 15.6-2.92 × 103 pg·m-3 and 3.90-27.4 pg·m-3, respectively, in which 6PPD and DNPD are the main compounds. Moreover, a competitive formation mechanism between sulfate, nitrate, ammonium (SNA) and 6PPD-Q was observed. The source apportionment results show that the incorporation of PPDs in PMF reduced the contribution of traffic source to PM2.5 from 13.5 % to 9.5 %. In the traffic source factor profiles, the load of IPPD, CPPD, DPPD, DNPD and 6PPD reaches 91.8 %, 91.6 %, 92.9 %, 80.6 % and 87.2 %, respectively. It`s amazing that traditional markers of traffic source, which often overlap with coal burning and industrial sources, over-estimated the contribution of vehicles by one third or more. The discovery of PPDs as specific markers for vehicular emissions holds significant utility, particularly considering the growing proportion of new energy vehicles in the future. The results may prove more accurate policy implications for pollution control. SYNOPSIS: PPDs are excellent indicators of vehicle emissions, and PMF without PPDs over-estimated the contribution of traffic source to PM2.5.

Refractive error and abnormal stereopsis association with road traffic accidents in Saudi Arabian truck drivers.

PURPOSE: To investigate the visual functions of truck drivers of the Kingdom of Saudi Arabia (KSA) in the region of Qassim and Dammam and to see if is there any association between these visual functions and self-reported road traffic accidents (RTA). METHODS: It is a cross-sectional, descriptive study. LogMAR visual acuity, refractive error, color vision, stereopsis, and confrontation visual fields were measured in 300 truck drivers in the Qassim and Dammam regions of KSA. Driving-related history and incidence of RTA from the past 3 years, systemic history, and general eye compliance history were collected through a self-reporting questionnaire. RESULTS: Among 300 truck drivers examined, 54 (18.4%) subjects have a refractive error, 14 (4.7%) subjects have color vision deficiency, 37 (12.2%) subjects have abnormal stereo acuity, and none of them have confrontation visual field defect. RTA was reported in 25 (8.3%) subjects. The current study has found RTA is significantly associated with refractive error (P = 0.01) and abnormal stereopsis (P < 0.01). Systemic history revealed that 11% of the subjects had diabetes mellitus. CONCLUSION: The current study is the first to report on the visual functions of KSA truck drivers. Hence, the current study has found a significant association between visual functions and RTA among truck drivers, we recommend a comprehensive examination need to be part of issuing driver's licenses in KSA. More studies with larger samples from different regions of KSA are needed to extrapolate these findings.

Attitudes and experiences of traditional Korean medicine practitioners in cases of traffic accidents: A qualitative study.

Objective: The surge in vehicles has escalated traffic volume, leading to an upswing in traffic accidents and subsequent disorders. Complex symptoms often characterize post-traumatic syndrome from these accidents. Traditional Korean medicine (TKM), increasingly used in car insurance, forms a substantial part of treatment costs. However, the current system lacks explicit fee guidelines and approval criteria for non-reimbursable TKM procedures, relying heavily on practitioners' judgment without robust evidence-based decision-making. This scenario raises concerns about treatment appropriateness and transparency. We aim to explore physicians' perspectives on utilizing TKM in emergency medicine, their participation sentiments, and their session selection process post-traffic accident. Methods: We collected TKM practitioners' opinions regarding their role in clinical environment and involvement in treating patients after traffic accidents. The need for comprehensive and standardized protocols for the diagnosis, treatment, management, and prognosis of patients with post-traumatic syndrome is evident. Additionally, improvements that facilitate rational decision-making by medical consumers and protect the treatment rights of healthcare providers are necessary. Results has emphasized the importance of evidence-based decision-making, establishing appropriate fee structures and detailed criteria for non-reimbursable TKM-based procedures, and enhancing regulations for the reliability and transparency of TKM-based treatments in the context of car insurance. Results and conclusions: The perspective of healthcare providers directly involved in TKM-based treatments must be considered to maintain a sustainable vehicular insurance system, transcending administrative policy discourse. We highlighted the challenges and potential solutions for improving the effectiveness and appropriateness of TKM-based treatments in the context of car insurance.

Demographic characteristics and trends of cell phone use while driving citations in selected states in the United States, 2010-2020.

OBJECTIVE: Distracted driving is a leading cause of motor vehicle crashes, and cell phone use is a major source of in-vehicle distraction. Many states in the United States have enacted cell phone use laws to regulate drivers' cell phone use behavior to enhance traffic safety. Numerous studies have examined the effects of such laws on drivers' cell phone use behavior based on self-reported and roadside observational data. However, little was known about who actually violated the laws at the enforcement level. This study sought to uncover the demographic characteristics of drivers cited for cell phone use while driving and whether these characteristics changed over time since the enactment of cell phone laws. METHODS: We acquired useable traffic citation data for 7 states in the United States from 2010 to 2020 and performed descriptive and regression analyses. RESULTS: Male drivers were cited more for cell phone use while driving. Handheld and texting bans were associated with a greater proportion of cited drivers aged 40 and above, compared to texting-only bans. Trends in the citations issued based on drivers' age group following the enactment of different cell phone laws were also uncovered. The proportion of citations issued to drivers aged 60 and above increased over time but the temporal trend remained insignificant when population effect was considered. CONCLUSIONS: This study examined the demographic characteristics of drivers cited for cell phone use while driving in selected states with texting-only bans or handheld and texting bans. The results reveal policy-based differences in trends in the proportion of citations issued to drivers in different age groups.

Controlled human exposures to diesel exhaust or particle-depleted diesel exhaust with allergen modulates transcriptomic responses in the lung.

The evidence associating traffic-related air pollution (TRAP) with allergic asthma is growing, but the underlying mechanisms for this association remain unclear. The airway epithelium is the primary tissue exposed to TRAP, hence understanding its interactions with TRAP and allergen is important. Diesel exhaust (DE), a paradigm of TRAP, consists of particulate matter (PM) and gases. Modern diesel engines often have catalytic diesel particulate filters to reduce PM output, but these may increase gaseous concentrations, and their benefits on human health cannot be assumed. We conducted a randomized, double-blinded, crossover study using our unique in vivo human exposure system to investigate the effects of DE and allergen co-exposure, with or without particle depletion as a proxy for catalytic diesel particulate filters, on the airway epithelial transcriptome. Participants were exposed for 2 h before an allergen inhalation challenge, with each receiving filtered air and saline (FA-S), filtered air and allergen (FA-A), DE and allergen (DE-A), or particle-depleted DE and allergen (PDDE-A), over four different occasions, each separated by a 4-week washout period. Endobronchial brushings were collected 48 h after each exposure, and total RNA was sequenced. Differentially expressed genes (DEGs) were identified using DESeq2, followed by GO enrichment and pathway analysis. FA-A, DE-A, and PDDE-A exposures significantly modulated genes relative to FA-S, with 462 unique DEGs identified. FA-A uniquely modulated the highest number (↑178, ↓155), followed by DE-A (↑44, ↓23), and then PDDE-A exposure (↑15, ↓2); 6 DEGs (↑4, ↓2) were modulated by all three conditions. Exposure to PDDE-A resulted in modulation of 285 DEGs compared to DE-A exposure, further revealing 26 biological process GO terms, including "cellular response to chemokine" and "inflammatory response". The transcriptional epithelial response to diesel exhaust and allergen co-exposure is enriched in inflammatory mediators, the pattern of which is altered upon particle depletion.

Drink and drive? Understanding the dynamics of youth risk-taking.

We exploit a reduction in the minimum legal drinking age (MLDA) in New Zealand from 20 to 18 to study the dynamics of youth risk-taking. Using the universe of road accidents over 15 years and an event history approach, we find no evidence that lowering the drinking age increased alcohol-related accidents among teens. Complementary results of a cohort analysis suggest that reducing the drinking age even led to a short-term decline in risky driving among youths directly affected by the MLDA change but had no longer-run impacts on youth risky driving and drinking behaviors.

Evaluation of Adolescents' Awareness of Seat Belt Use and the Relationship with Risky Behaviors.

The one of the leading causes of adolescent morbidity and mortality worldwide is motor vehicle accidents (MVA). The use of seat belts significantly lowers MVA fatalities and injuries. The aim of this study is to investigate adolescent seat belt usage patterns and relation with risky behaviors. The study conducted at two medical institutions with non-immigrant and literate adolescents aged 12-18. Demographics, seat belt use, and risk-taking behavior were collected through questionnaires. 726 teenagers (422 girls and 304 boys) with an average age of 176.7 ± 23.37 months participated in the study. Parents' educational levels and front-seat belt use have been found to be correlated. Comparatively to non-users, seat belt users demonstrated lower risk scores (total, traffic, substance, and social). The use of seat belts was significantly predicted by traffic risk, according to logistic regression. The frequency of seatbelt use was higher among participants from cities with higher socioeconomic status. As a result, it was found that adolescents who exhibited more risky behaviors had a lower frequency of seat belt use and seat belt use was associated with socioeconomic level and parental education level. It is thought that population-based studies to be conducted on this subject are important.

Road traffic accidents and the contributing factors among drivers of public transportation in Mizan Aman town, Ethiopia: a Community-Based Cross-Sectional Study.

Background: Traffic accidents on the road is an accident is a terrible accident that causes death, injury, and property damage. However, limited studies were addressed to investigate the prevalence of traffic accidents on the road and the contributing factors among drivers that help in developing strategies to cop-up the incidence within the research domain in Ethiopia, particularly in the study area. Objective: This study aimed to assess the prevalence of road traffic accidents and the contributing factors among drivers of public transportation in Mizan Aman town, Ethiopia. Methods: A community-based cross-sectional survey was employed among 376 drivers of public transportation. Every research subject was selected by using a simple random sampling technique. Semi-structured and open-ended questionnaires which comprised demographic characteristics, risky personal behaviors and lifestyles, driver's factors, vehicle condition, and environmental conditions were used to gather data. And then after, data was collected through interviewer-administered using KoBo Collect tools. Completed data were edited and cleaned in the Kobo collect toolbox and then exported for additional analysis to a statistical tool for social science statistics version 26. The descriptive statistics were displayed as figures, tables, and texts. Binary logistic regression was analyzed to identify the contributing factors. Statistically significant was decided with a p-value of ≤ 0.05. Results: The results showed that the prevalence of road traffic accidents among drivers of public transportation in Mizan Aman town was 17%. The study identified factors influencing traffic accidents on the roads including marital status (being single), employee condition (permanent), monthly income (1001-2500 Ethiopia Birr), alcohol use, vehicle maintenance (not), road type (non-asphalt), and weather conditions (being windy). Conclusion: The overall prevalence of road traffic accidents among drivers of public transportation in Mizan Aman town was relatively low. Despite this, sociodemographic characteristics, driver factors, vehicle conditions, and environmental conditions [road type and weather conditions] were the predicting factors of traffic accidents in town. Therefore, reduction strategies should be the highest priority duty for concerned bodies like Mizan Aman town road and transport office, Bench Sheko zone transport and logistics office, and Southwest Ethiopia People Regional State (SWEPRS) transport bureau in the study area.

Enhancing Aviation Safety through AI-Driven Mental Health Management for Pilots and Air Traffic Controllers.

This article provides an overview of the mental health challenges faced by pilots and air traffic controllers (ATCs), whose stressful professional lives may negatively impact global flight safety and security. The adverse effects of mental health disorders on their flight performance pose a particular safety risk, especially in sudden unexpected startle situations. Therefore, the early detection, prediction and prevention of mental health deterioration in pilots and ATCs, particularly among those at high risk, are crucial to minimize potential air crash incidents caused by human factors. Recent research in artificial intelligence (AI) demonstrates the potential of machine and deep learning, edge and cloud computing, virtual reality and wearable multimodal physiological sensors for monitoring and predicting mental health disorders. Longitudinal monitoring and analysis of pilots' and ATCs physiological, cognitive and behavioral states could help predict individuals at risk of undisclosed or emerging mental health disorders. Utilizing AI tools and methodologies to identify and select these individuals for preventive mental health training and interventions could be a promising and effective approach to preventing potential air crash accidents attributed to human factors and related mental health problems. Based on these insights, the article advocates for the design of a multidisciplinary mental healthcare ecosystem in modern aviation using AI tools and technologies, to foster more efficient and effective mental health management, thereby enhancing flight safety and security standards. This proposed ecosystem requires the collaboration of multidisciplinary experts, including psychologists, neuroscientists, physiologists, psychiatrists, etc. to address these challenges in modern aviation.

Quality of Life and Socioeconomic Status in Northwest of Iran: First Wave of the Persian Traffic Cohort Study.

This study aimed to evaluate the association between Quality of Life (QOL) and independent factors, emphasizing Socio Economic Status (SES) in northwestern Iran. A population-based cross-sectional study was performed within the Persian Traffic safety and health Cohort in 2020. Participants were chosen using stratified random sampling method. The majority of participants (69%) were aged between 30 and 65. Around half of the participants were males (54.44%). Most of the female respondents were categorized as very low and medium levels of SES Based on multiple linear regression analysis, the QOL among females was lower compared to males (ß: - 0.92, 95% CI - 1.82 to - 0.22). There was a negative association between SES and QOL; individuals with low and very low levels of SES had a lower QOL than those with a medium level of SES (ß: - 4.38, 95% CI - 5.9 to - 2.86) (ß: - 2.65, 95% CI - 4.08 to - 1.22). The current study highlights that higher SES and educational levels are positively associated with higher QOL. Conversely, older age, females, and widowed individuals are linked with lower QOL.

Estimating near-roadway air pollution from multi-frequency noise measurements.

Air pollution is a major environmental problem and its monitoring is essential for regulatory purposes, policy making, and protecting public health. However, dense networks of air quality monitoring equipment are prohibitively expensive due to equipment costs, labor requirements, and infrastructure needs. As a result, alternative lower-cost methods that reliably determine air quality levels near potent pollution sources such as freeways are desirable. We present an approach that couples noise frequency measurements with machine learning to estimate near-roadway particulate matter (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) at 1-min temporal resolution. The models were based on data collected by co-located noise and air quality instruments near a busy freeway in Long Beach, California. Model performance was excellent for all three pollutants, e.g., NO2 predictions yielded Pearson's R = 0.87 with a root mean square error of 7.2 ppb; this error represents about 10 % of total morning rush hour concentrations. Among the best air pollutant predictors were noise frequencies at 40 Hz, 500 Hz, and 800 Hz, and meteorology, particularly wind direction. Overall, our method potentially provides a cost-effective and efficient approach to estimating and/or supplementing near-road air pollutant concentrations in urban areas at high temporal resolution.

Study on the risk assessment of Pedestrian-Vehicle conflicts in channelized Right-Turn lanes based on the Hierarchical-Grey Entropy-Cloud model.

Channelized right-turn lanes (CRTLs) in urban areas have been effective in improving the efficiency of right-turning vehicles but have also presented negative impacts on pedestrian movement. Pedestrians experience confusion regarding the allocation of road space when crossing crosswalks within these areas, leading to frequent conflicts between pedestrians and motor vehicles. In this paper, considering the characteristics of pedestrian-vehicle conflicts at channelized right-turn lanes as well as the ambiguity and uncertainty of the causes, a comprehensive assignment combined with a cloud model is proposed as a risk evaluation model for pedestrian-vehicle conflicts. The study established a risk indicator system based on three aspects of the transportation system: pedestrians, motor vehicles, and the road environment. Combining the analytic hierarchy process (AHP), grey relational analysis (GRA), and entropy weighting method (EWM) to get the weights of indicator combinations, and then using the cloud model to realize quantitative and qualitative language transformation to complete the risk evaluation. This study employs specific road segments in Qingdao as a validation case for model analysis. The results indicate that the model's evaluation outcomes exhibited a significant level of agreement with the findings from field investigations during both peak and off-peak periods. It is demonstrated that the model has good performance for the safety assessment of pedestrian-vehicle conflicts at CRTL, and it also reflects the ability of the model to assess fuzzy randomness problems. It provides participation value for urban pedestrian-vehicle safety problems as well as applications in other fields.