A comprehensive evaluation of the frog effect on drivers in mountain highway tunnels - The effect of low-volume intermittent information.

OBJECTIVE: The driver's inability to fully absorb and react to operational cues while driving is like boiling a frog in warm water. With intermittent, low-volume information, drivers can underreact by ignoring these minor but continuous changes. This paper aims to provide an opportunity to test the effects of intermittently occurring low-volume information on drivers. METHODS: A real vehicle test with naturalistic driving was used to collect driving speed data from 40 drivers on a highway tunnel section in Chongqing, China, where nine tunnels are located. Drivers were classified into three categories according to the degree of compliance of their driving speed with the speed limit required by traffic signs, and drivers were analyzed in terms of their sensitivity to traffic signs and their reaction to driving maneuvers. RESULTS: Conservative drivers are the most absorbent of low-volume intermittent information, and the cumulative effect of the frog effect does not exceed 2.00 km; eager drivers tend to ignore this information, and the cumulative effect of the frog effect reaches 2.91 km; and the general type of driver is in the middle of these two types of drivers, and the frog effect gradually penetrates the driving speed in a weakly increasing manner, up to a maximum of 9.8 km. CONCLUSION: At the beginning of a journey, drivers are most sensitive to traffic signs, and low-volume intermittent information can also play a role in guiding driving operations effectively at this time. However, as the driving distance increases, the effect of the frog effect on different types of drivers gradually increases, even exceeding the effect caused by the black-and-white hole effect, especially when driving in tunnel groups. Considering the driving characteristics of different types of drivers to improve the deployment of low-volume intermittent information and reduce the distance of the frog effect can effectively improve driving safety.

Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution.

Traffic flow prediction is crucial for efficient traffic management. It involves predicting vehicle movement patterns to reduce congestion and enhance traffic flow. However, the highly non-linear and complex patterns commonly observed in traffic flow pose significant challenges for this task. Current Graph Neural Network (GNN) models often construct shallow networks, which limits their ability to extract deeper spatio-temporal representations. Neural ordinary differential equations for traffic prediction address over-smoothing but require significant computational resources, leading to inefficiencies, and sometimes deeper networks may lead to poorer predictions for complex traffic information. In this study, we propose an Adaptive Decision spatio-temporal Neural Ordinary Differential Network, which can adaptively determine the number of layers of ODE according to the complexity of traffic information. It can solve the over-smoothing problem better, improving overall efficiency and prediction accuracy. In addition, traditional temporal convolution methods make it difficult to deal with complex and variable traffic time information with a large time span. Therefore, we introduce a multi-kernel temporal dynamic expansive convolution to handle the traffic time information. Multi-kernel temporal dynamic expansive convolution employs a dynamic dilation strategy, dynamically adjusting the network's receptive field across levels, effectively capturing temporal dependencies, and can better adapt to the changing time data of traffic information. Additionally, multi-kernel temporal dynamic expansive convolution integrates multi-scale convolution kernels, enabling the model to learn features across diverse temporal scales. We evaluated our proposed method on several real-world traffic datasets. Experimental results show that our method outperformed state-of-the-art benchmarks.

Impacts of the Chengdu 2021 world university games on NO2 pollution: Implications for urban vehicle electrification promotion.

Emissions of nitrogen oxides (NOx) are a dominant contributor to ambient nitrogen dioxide (NO2) concentrations, but the quantitative relationship between them at an intracity scale remains elusive. The Chengdu 2021 FISU World University Games (July 22 to August 10, 2023) was the first world-class multisport event in China after the COVID-19 pandemic which led to a substantial decline in NOx emissions in Chengdu. This study evaluated the impact of variations in NOx emissions on NO2 concentrations at a fine spatiotemporal scale by leveraging this event-driven experiment. Based on ground-based and satellite observations, we developed a data-driven approach to estimate full-coverage hourly NO2 concentrations at 1 km resolution. Then, a random-forest-based meteorological normalization method was applied to decouple the impact of meteorological conditions on NO2 concentrations for every grid cell, the resulting data were then compared with the timely bottom-up NOx emissions. The SHapley-Additive-exPlanation (SHAP) method was employed to delineate the individual contributions of meteorological factors and various emission sources to the changes in NO2 concentrations. According to the full-coverage meteorologically normalized NO2 concentrations, a decrease in NOx emissions and favorable meteorological conditions accounted for 80 % and 20 % of the NO2 reduction, respectively, across Chengdu city during the control period. Within the strict control zone, a 30 % decrease in the meteorologically normalized NO2 concentrations was observed during the control period. The normalized NO2 concentrations demonstrated a strong correlation with NOx emissions (R = 0.96). Based on the SHAP analysis, traffic emissions accounted for 73 % of the reduction in NO2 concentrations, underscoring the significance of traffic control measures in improving air quality in urban areas. This study provides insights into the relationship between NO2 concentrations and NOx emissions using real-world data, which implies the substantial benefits of vehicle electrification for sustainable urban development.

Investigating Implicit and Explicit Communication of Highly Automated Vehicles in Japan: How do Light-band eHMIs affect Pedestrians' Willingness to Cross, Trust and Perceived Safety?

In the near future, pedestrians will face highly automated vehicles on the roads. Highly automated vehicles (HAVs) should have safety-enhancing communication tools to guarantee traffic safety, e.g., vehicle kinematics and external human-machine interfaces (eHMIs). Pedestrians, as highly vulnerable road users, depend on communication with HAVs. Miscommunication between pedestrians and HAVs could quickly result in accidents, and this, in turn, could cause severe impairments for pedestrians. Light-band eHMIs have the potential to enhance traffic safety. However, eHMIs have been less explored in Japan so far. As a first-time approach, this experimental online study shed light on the effect of a light-band eHMI on Japanese pedestrians (N=99). In short video sequences, the participants interacted with two differently sized HAVs equipped with light-band eHMI. We investigated the effect of vehicle size (small vs. large), eHMI status (no eHMI vs. static eHMI vs. dynamic eHMI), and vehicle kinematics (yielding vs. non-yielding) on pedestrians' willingness to cross, trust, and perceived safety. To investigate possible side effects of eHMIs, we also included experimental conditions in which the eHMI mismatched the vehicle's kinematics. Results revealed that Japanese were more willing to cross the street and indicated higher trust- and safety ratings when they received information about the vehicle's intention and automation status (dynamic eHMI) compared to when they received no information (no eHMI) or only about the vehicle automation status (static eHMI). Surprisingly, Japanese participants tended to rely on the eHMI when there was mismatching information between eHMI and vehicle kinematics. Overall, we concluded that light-band eHMIs could contribute to a safe future interaction between pedestrians and HAVs in Japan under the requirement that the eHMI is in accordance with vehicle kinematics.

Capturing Exposure Disparities with Chemical Transport Models: Evaluating the Suitability of Downscaling Using Land Use Regression.

High resolution exposure surfaces are essential to capture disparities in exposure to traffic-related air pollution in urban areas. In this study, we develop an approach to downscale Chemical Transport Model (CTM) simulations to a hyperlocal level (∼100m) in the Greater Toronto Area (GTA) under three scenarios where emissions from cars, trucks and buses are zeroed out, thus capturing the burden of each transportation mode. This proposed approach statistically fuses CTMs with Land-Use Regression using machine learning techniques. With this proposed downscaling approach, changes in air pollutant concentrations under different scenarios are appropriately captured by downscaling factors that are trained to reflect the spatial distribution of emission reductions. Our validation analysis shows that high-resolution models resulted in better performance than coarse models when compared with observations at reference stations. We used this downscaling approach to assess disparities in exposure to nitrogen dioxide (NO2) for populations composed of renters, low-income households, recent immigrants, and visible minorities. Individuals in all four categories were disproportionately exposed to the burden of cars, trucks, and buses. We conducted this analysis at spatial resolutions of 12, 4, 1 km, and 100 m and observed that disparities were significantly underestimated when using coarse spatial resolutions. This reinforces the need for high-spatial resolution exposure surfaces for environmental justice analyses.

Cannabis policy bundles and traffic fatalities in the American States over time.

BACKGROUND AND AIM: Since 1996, 38 US states have legalized access to cannabis (medical and/or adult-use recreational). We aimed to estimate the effect of three dimensions of state cannabis policy design - pharmaceutical, permissive and fiscal - on levels of overall, alcohol-impaired, occupant, light truck and pedestrian fatality rates. DESIGN AND SETTING: Observational study of US states' overall, alcohol-impaired, occupant, light truck and pedestrian fatalities between 1994 and 2020. CASES: The unit of analysis was at the state level, consisting of 50 states and 27 years of time series data, resulting in a total of 1350 state-year observations. MEASUREMENTS: Fatality rates associated with alcohol-impaired, pedestrian, total occupant, passenger car and light truck fatality rates were obtained from the Fatality Analysis Reporting System of the National Highway Traffic Safety Administration and normalized per 10 billion vehicle miles traveled. State cannabis policies are measured in three bundles (scales): pharmaceutical, permissive and fiscal. FINDINGS: The pharmaceutical bundle was associated with increases in all fatality rates [ß = 0.145; 95% confidence interval (CI) = 0.116-0.173; P < 0.000]. The permissive bundle was associated with lower overall fatality rates (ß = -0.319; 95% CI = -0.361 to -0.277; P < 0.000). The fiscal bundle was generally associated with higher fatality rates (ß = 0.062; 95% CI = 0.043-0.081; P < 0.000), occupant (ß = 0.070; 95% CI = 0.042-0.098; P < 0.000), light trucks (ß = 0.049; 95% CI = 0.026-0.072; P < 0.000). CONCLUSIONS: US state cannabis regulations influence traffic safety. Greater permissiveness in US state cannabis regulations does not appear to correlate with traffic fatality rate increases, but greater medicalization and fiscal operation does.

Obstructive shock induced by internal thoracic artery injury with traumatic sternal fracture.

Internal thoracic artery (ITA) injuries associated with sternal fractures can lead to shock. Several studies have documented injuries resulting in hemorrhagic shock, yet there is limited reporting on obstructive shock. Opinions differ regarding which is superior between transcatheter arterial embolization (TAE) and open thoracotomy. We report the case of an 80-year-old female patient presented with blunt chest trauma when driving. Her vital signs were normal. However, ultrasonography revealed a hypoechoic anterior mediastinal lesion. Her blood pressure decreased immediately before undergoing a computed tomography (CT) scan. The CT scan showed a sternal fracture, anterior mediastinal extravasation, and dilation of the inferior vena cava. TAE was performed on both internal thoracic arteries, and the patient was transferred to a hospital where an open thoracotomy could be performed. The patient was treated conservatively and discharged without sequelae. Obstructive shock caused by an ITA injury with a sternal fracture can be successfully treated using TAE.

Cholinergic stimulation stabilizes TRPM4 in the plasma membrane of cortical pyramidal neurons.

TRPM4 is a calcium activated non-selective cation channel, impermeable to Ca2+, in neurons it has been implicated in the regulation of the excitability and in the persistent firing. Cholinergic stimulation is also implicated in changes in excitability that leads neurons to an increased firing frequency, however it is not clear whether TRPM4 is involved in the cholinergic-induced increase in firing frequency. Here using a combination of patch clamp electrophysiology, Ca2+ imaging, immunofluorescence, fluorescence recovery after photobleaching (FRAP) and pharmacological approach, we demonstrate that carbachol (Cch) increases firing frequency, intracellular Ca2+ and that TRPM4 inhibition using 9-Ph and CBA reduces firing frequency and decreases the peak in intracellular Ca2+ induced by Cch in cortical pyramidal neurons in culture. Moreover, we determined that cholinergic stimulation reduces TRPM4 recycling and stabilizes TRPM4 in the plasma membrane. Together our results indicate that cholinergic stimulation increases firing in a TRPM4 dependent manner, and also increases the TRPM4 stability in the membrane, suggesting that TRPM4 is locked in microdomains in the membrane, possibly signaling or cytoskeleton proteins complexes.

Prevalence of Urogenital Injury following Road Accident: A Systematic Review.

INTRODUCTION AND HYPOTHESIS: Trauma complications have been one of the most serious public health concerns worldwide. In most reports, urogenital injuries (UGIs) are seen in approximately 10% of adult traumatic patients and less than 3% of children with multiple/severe trauma to the abdomen or pelvis. Traffic accidents are the most common cause of UGIs. The purpose of this study is to systematically determine the prevalence and types of UGIs after car accidents. METHODS: The search strategy was aimed at finding relevant studies in October 2023. No restrictions on language or date were applied. The following criteria were considered eligibility criteria: reporting at least one epidemiological aspect of UGIs in people with road traffic injury (RTI) and a separate epidemiological analysis of RTIs in UGI (we also included those articles that pointed out all RTIs but separately mentioned UGIs). Two experts assessed the reporting quality of articles using standardized critical appraisal instruments from the Joanna Briggs Institute. Statistical analysis for this study was conducted using the CMA statistical software version 3.2.0. RESULTS: A total of 1,466,024 cases following RTIs through 107 studies were included in our review. Of these, 29 studies were related to children (20,036), and the others reported RTIs in adults (1,445,988). The total prevalence was 4.7%, and car accidents were responsible in 36 studies, followed by motorcycle accidents in 25, bicycles in 17 studies, and automobile-pedestrian collisions in 23 related studies. In subgroup analysis based on the damaged organ, the rate of bladder injury was 3.5%. This rate was 5.3% for kidneys. CONCLUSION: This systematic review and meta-analysis found that the prevalence of UGI following RTIs was 4.7%, with car accidents being the most common cause. UGIs were more prevalent in adults than in children, and bladder and kidney injuries were the most commonly reported types. The prevalence of UGI varied by country and study design.

Ten years of oil pollution detection in the Eastern Mediterranean shipping lanes opposite the Egyptian coast using remote sensing techniques.

The Eastern Mediterranean region, a vital conduit for global maritime trade, faces significant environmental challenges due to marine pollution, particularly from oil spills. This is the first study covering the long period of comprehensive monitoring of oil pollution using the full mission of Sentinel-1 Synthetic Aperture Radar (SAR) data in the Mediterranean Sea, so this research aims to detect and analyze comprehensively the occurrence of oil spills in the Eastern Mediterranean over a decade (2014-2023). This study focuses on identifying geographical distribution patterns, proximity to shorelines, frequency across maritime zones, and potential sources of these spills, especially around major ports and maritime routes. This study utilizes SAR data from the Sentinel-1 satellite. The methodology included automated detection algorithms within the Sentinel application platform (SNAP) and integration with GIS mapping to study oil spill patterns and characteristics. Over 1000 Sentinel-1 scenes were investigated in the northern Mediterranean waters off the coast of Egypt, to detect and analyze 355 oil spill events with a total impacted area of more than 6000 km2. The analysis of temporal spill distribution reveals significant fluctuations from year to year. Within the entire timeline of the study, 2017 had the largest spatial areas covering one thousand square kilometers. In contrast, the single largest spill recorded during the study period occurred in 2020, covering 198.73 square kilometers. The results identified a non-uniform distribution of oil spills and primarily exhibiting elongated patterns aligned with the navigation routes. The distinct increase of oil spill incidents was within the Exclusive Economic Zone (EEZ), obviously drifted to the coastline and around major ports. The study emphasizes the critical role of remote sensing technologies in addressing environmental challenges caused by the maritime transport sector, advocating for enhanced monitoring and regulatory enforcement to protect marine ecosystems and support sustainable naval activities. The findings highlight the urgent need for targeted continuous monitoring and rapid response strategies in high-traffic maritime areas, particularly around the EEZ and major ports.

Chinese adaptation of the reckless driving behaviour scale: Testing its psychometric properties and links with safe driving climate among family and peers.

Purpose: The present study aimed to revise the Reckless Driving Behaviour Scale (RDBS) and examined its reliability and validity among young Chinese drivers. Methods: The RDBS, the Safe Driving Climate among Friends Scale (SDCaF), the Family Climate for Road Safety Scale (FCRSS) and a social desirability scale were administrated to 560 young drivers. Exploratory factor analysis (EFA, n = 250) and confirmatory factor analysis (CFA, n = 250) were conducted to examine the factorial structure of the RDBS. Results: The Chinese version of the RDBS has 18 items that are divided into 4 factors: distraction, substance use, extreme behaviour and positioning. Both the results of EFA and CFA confirmed its factorial structure. The reliability of the RDBS was acceptable and the concurrent validity of the scale was supported by its significant associations with the SDCaF and FCRSS factors. Finally, drivers who had violation involvement scored higher on all four factors than their peers who did not have violation involvement, providing evidence for its known-group validity. Conclusion: The revised RDBS has similar structure with the original version and its reliability and validity were satisfactory. It is an effective tool to measure the reckless driving behaviour of young drivers in China and interventions that incorporated joint efforts of family and peers should be developed.

Quality of life of survivors following road traffic orthopaedic injuries in Rwanda.

Background: Road traffic injuries (RTI) pose a global public health threat, especially in low- and middle-income nations. These injuries typically cause orthopaedic problems that may negatively impair a person's physical and mental health and quality of life. Our study examined the quality of life of road traffic orthopaedic injuries (RTOI) survivors. Methods: A cross-sectional study at five Rwandan referral hospitals, included 369 adult RTOI victims. Two years post-injury, participants completed the European Quality of life 5 Dimension 5 (EQ-5D-5L) and Visual Analogue Scale (VAS) Questionnaire between June 2 and August 31, 2022, with informed consent. Three EQ-5D-5L-VAS scores were used: low (0-40%), fair (41-60%), and excellent (61-100%). We used logistic regression analysis with a significance threshold of p < 0.05 to determine odds ratios (OR) and 95% CI. Results: The RTOI victims had a mean age of 37.5 ± 11.26 years with sex ratio M:F:3:1. Usual activities (66.8%) and mobility (54.8%) were the most affected EQ-5D-5L dimensions. Residence, hospital stay, rehabilitation, and return to work affected mobility, usual activities, pain/discomfort, and anxiety/depression. The EQ-5D-5L/VAS score showed 34.95% poor QoL (0-40%) and 35.50% good QoL. Factors affecting QoL include level of education (OR = 1.66, p < <0.01), type of intervention (OR = 1.22, p = 0.003), rehabilitation (OR = 2.41, p < 0.01) and level of disability (OR = 196.41, p < 0.01). Mobility, self-care, usual activities, pain, comfort, anxiety, and depression vary moderately on Shannon's index. Conclusion: The study highlights the significant impact of road traffic orthopaedic injuries (RTOI) on survivors' quality of life in Rwanda, revealing challenges in mobility and daily activities. Factors influencing quality of life include education level, medical intervention type, rehabilitation, and disability degree. The findings emphasize the need for tailored rehabilitation strategies and policy interventions to improve long-term outcomes for RTOI survivors.

Numerical simulation of the transition flight aerodynamics of cross-shaped quad-tiltrotor UAV.

In order to enhance the stability of the tilt transition process, a new configuration of Quad-Tiltrotor UAV was presented in this paper. Firstly, numerical simulation was used to calculate and analyze the aerodynamic interaction between the front rotor/fuselage/rear rotor during the transition state mode. The calculation model of the isolated rotor, front-rear rotor, front rotor-fuselage, and front rotor-rear rotor-fuselage combination states are established. Besides, the effects of pitch, roll, and yaw moment on the fuselage at different tilt angles are analyzed. It is concluded that the front rotor is the leading factor in the aerodynamic interference of the whole UAV in the different combination states. The research results can provide a reference for the optimization design of the overall layout, structure, and flight control strategy of the cross-shaped quad-tiltrotor UAV, and can also provide solutions for the logistics application of urban air traffic.

Polycyclic aromatic hydrocarbons (PAHs) in blood serum of adults living in high and low-traffic volume areas in Malaysia: A comparative cross-sectional study.

Ambient polycyclic aromatic hydrocarbons (PAHs) originate predominantly from fuel combustion of motor vehicles and have the potential to affect human health. However, there is insufficient knowledge regarding serum PAHs health risks among the Malaysian population. This study aims to compare PAH concentrations, distributions, correlations, and health risks in 202 blood serum samples drawn from residents living in high-traffic volume areas (Kuala Lumpur) and low-traffic volume areas (Hulu Langat) in Malaysia. Solid phase extraction and gas chromatography-mass spectrometry (GC-MS) were employed to extract and analyze blood serum samples. Questionnaires were distributed to obtain sociodemographic and contributing factors of serum PAHs. The mean total PAHs concentration in serum of the Kuala Lumpur group was 54.44 ng g-1 lipids, double the Hulu Langat group's concentration (25.7 ng g-1 lipids). Indeno(1,2,3-cd)pyrene (IcP) and acenaphthene (ACP) feature the most and least abundant compounds in both study groups. The mean concentrations of IcP and ACP in the Kuala Lumpur and Hulu Langat groups were 26.8 vs 12.68 and 0.27 vs 0.14 ng g-1 lipids, respectively. High-molecular-weight PAHs (HMW-PAHs) composed 85% of serum total PAHs in both groups. Significant correlations were found (i) between the individual serum PAH congeners (p<0.01) and (ii) between serum PAHs and total lipids (p<0.01). According to the questionnaire data, high traffic volume and outdoor hobbies were the only contributory factors that confirmed significant relationships with serum PAHs (p<0.001). Health risk assessment was computed using benzo(a)pyrene (BaP) equivalent (BaPeq) and demonstrated that the Kuala Lumpur group has twofold greater carcinogenic risk than the Hulu Langat group (16.11 vs 7.76 ng g-1 lipids). Our study reveals that traffic volumes notably impact serum PAH levels and general health among the Malaysian population.

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.

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.

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.

The epidemiology and outcomes of severe road traffic injury by road user type in Korea: A nationwide retrospective observational study.

OBJECTIVES: Road traffic injuries (RTIs) pose a significant public health burden, and more than half of these fatalities are attributed to vulnerable road users (VRUs). This study aimed to evaluate the epidemiology and outcomes of severe RTIs in Korea by focusing on different types of road users. METHODS: This is nationwide retrospective observational study. Using data from the Korean Nationwide Severe Trauma Registry, this study analyzed severe RTI cases from 2016 to 2020. The study included EMS-treated severe trauma patients, defining severe RTI as cases with an injury severity score (ISS) ≥16 or out-of-hospital cardiac arrest (OHCA). The main variable of interest was the road user type, classified as motor vehicle occupants (MVOs), pedestrians, motorcyclists, and bicyclists. Trends and injury characteristics by road user type were analyzed, and multivariate logistic regression was conducted to calculate the adjusted odds ratios (AORs) and 95 % confidence intervals (CIs) of road user type for in-hospital mortality. RESULTS: Of the 143,021 EMS-treated severe trauma cases, 24,464 were included in this study. Pedestrians represented the largest group (n = 8,782; 35.9 %). More than half of the patients died (n = 12,620, 51.6 %), and a high proportion of patients had OHCA (n = 10,048, 41.1 %). There was no significant change in the overall severe RTI numbers from 2016 to 2020, but a decrease in pedestrian cases and an increase in motorcyclist cases were noted (both p for trend<0.05). Low usage of safety devices was observed (28.2 % of motor vehicle occupants used seat belts, 35.9 % of motorcyclists used helmets, and 9.6 % of bicyclists used helmets). Head injuries were most common, particularly among bicyclists (77.0 %) and motorcyclists (69.8 %). Compared to motor vehicle occupants, pedestrians (AOR [95 % CI] 1.12 [1.04-1.20]) and others (AOR [95 % CI] 1.30 [1.02-1.65]) had higher odds of mortality, while motorcyclists (AOR [95 % CI] 0.64 [0.59-0.69]) and bicyclists (AOR [95 % CI] 0.68 [0.60-0.76]) had lower odds of mortality. CONCLUSION: We found varying trends and injury characteristics in severe RTIs according to road user type. Adapting prevention strategies for evolving road user patterns, with particular attention to increasing safety device usage and addressing the high mortality associated with severe RTIs are warranted.

Bayesian hybrid gamma-GPD model for extreme traffic conflict threshold determination in the peak over threshold approach.

Extreme value theory (EVT) models have been frequently utilized to estimate crash risk from traffic conflicts with the peak over threshold commonly used to identify conflict extremes. However, a common problem for the peak over threshold method is the selection of a suitable threshold to distinguish general and extreme conflicts. Subjective and arbitrary selection of the threshold in peak over threshold method can result in bias and unstable estimation results. The primary objective of the study is to propose a hybrid modelling approach for the threshold determination in peak over threshold method. The hybrid model consists of a joint gamma distribution and generalized Pareto distribution (GPD). The gamma distribution is used to fit general conflicts while the GPD is used to fit extreme conflicts. Specially, discontinued, continued and differentiable gamma-GPD models are developed with the threshold being treated as a model parameter. Traffic conflict data collected from three signalized intersections in the city of Surrey, British Columbia were used for the study. The modified time to collision (MTTC) was employed as conflict indicator. The Bayesian approach was employed to estimate the threshold as well as other hybrid gamma-GPD model parameters. The results show that the discontinued gamma-GPD model is superior to the continued and differentiable gamma-GPD models for determining the threshold in terms of crash estimation accuracy and model fit. The crash estimates using the threshold determined by the hybrid gamma-GPD model outperform those estimated based on the traditional quantile plots method, indicating that the superiority of the proposed threshold determination approach based on gamma-GPD hybrid model. The proposed hybrid gamma-GPD model could determine the threshold parameter in peak over threshold method for traffic conflicts extremes automatically in an objective and quantitative way. It contributes to existing peak over threshold method for producing reliable crash estimation.