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)

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.

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.

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.

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.

Analysis of pedestrian accident severity by considering temporal instability and heterogeneity.

The aim of this study was to investigate the effects of temporal instability and possible heterogeneity on pedestrian accident severity, 48786 accident data from 2018 to 2021 in the UK STATS database were used as the study object, and accident severity was used as the dependent variable, and 49 accident characteristics were selected as independent variables from 6 characteristics of accident pedestrian, driver, vehicle, road, environment and time to construct the pedestrian accident mean heterogeneity random-parameter logit model and examined its temporal stability. The results of model estimation and likelihood ratio tests indicate that the variables affecting pedestrian injury severity are highly variable and not stable over the years. And further demonstrates the potential of models that address unobserved heterogeneity for significant relationships in pedestrian accident severity analyses.

GSOOA-1DDRSN: Network traffic anomaly detection based on deep residual shrinkage networks.

One of the critical technologies to ensure cyberspace security is network traffic anomaly detection, which detects malicious attacks by analyzing and identifying network traffic behavior. The rapid development of the network has led to explosive growth in network traffic, which seriously impacts the user's information security. Researchers have delved into intrusion detection as an active defense technology to address this challenge. However, traditional machine learning methods struggle to capture complex threats and attack patterns when dealing with large-scale network data. In contrast, deep learning methods have the advantages of automatically extracting features from network traffic data and strong generalization capabilities. Aiming to enhance the ability of network anomaly traffic detection, this paper proposes a network traffic anomaly detection based on Deep Residual Shrinkage Network (DRSN), namely "GSOOA-1DDRSN". This method uses an improved Osprey optimization algorithm to select the most relevant and essential features in network traffic, reducing the features' dimensionality. For better detection performance of network traffic anomalies, a one-dimensional deep residual shrinkage network (1DDRSN) is designed as a classifier. Validation is performed using the NSL-KDD and UNSW-NB15 datasets and compared with other methods. The experimental results show that GSOOA-1DDRSN has improved multi-classification accuracy, precision, recall, and F1 Score by approximately 2 % and 3 %, respectively, compared to the 1DDRSN model on two datasets. Additionally, it reduces the time computation costs by 20 % and 30 % on these datasets. Furthermore, compared to other models, GSOOA-1DDRSN offers superior classification accuracy and effectively reduces the number of features.

Understanding the Burden of Pediatric Traumatic Injury in Uganda: A Multicenter, Prospective Study.

INTRODUCTION: Traumatic injury is responsible for eight million childhood deaths annually. In Uganda, there is a paucity of comprehensive data describing the burden of pediatric trauma, which is essential for resource allocation and surgical workforce planning. This study aimed to ascertain the burden of non-adolescent pediatric trauma across four Ugandan hospitals. METHODS: We performed a descriptive review of four independent and prospective pediatric surgical databases in Uganda: Mulago National Referral Hospital (2012-2019), Mbarara Regional Referral Hospital (2015-2019), Soroti Regional Referral Hospital (SRRH) (2016-2019), and St Mary's Hospital Lacor (SMHL) (2016-2019). We sub-selected all clinical encounters that involved trauma. The primary outcome was the distribution of injury mechanisms. Secondary outcomes included operative intervention and clinical outcomes. RESULTS: There was a total of 693 pediatric trauma patients, across four hospital sites: Mulago National Referral Hospital (n = 245), Mbarara Regional Referral Hospital (n = 29), SRRH (n = 292), and SMHL (n = 127). The majority of patients were male (63%), with a median age of 5 [interquartile range = 2, 8]. Chiefly, patients suffered blunt injury mechanisms, including falls (16.2%) and road traffic crashes (14.7%) resulting in abdominal trauma (29.4%) and contusions (11.8%). At SRRH and SMHL, from which orthopedic data were available, 27% of patients suffered long-bone fractures. Overall, 55% of patients underwent surgery and 95% recovered to discharge. CONCLUSIONS: In Uganda, non-adolescent pediatric trauma patients most commonly suffer injuries due to falls and road traffic crashes, resulting in high rates of abdominal trauma. Amid surgical workforce deficits and resource-variability, these data support interventions aimed at training adult general surgeons to provide emergency pediatric surgical care and procedures.

Atlastin-1 regulates endosomal tubulation and lysosomal proteolysis in human cortical neurons.

Mutation of the ATL1 gene is one of the most common causes of hereditary spastic paraplegia (HSP), a group of genetic neurodegenerative conditions characterised by distal axonal degeneration of the corticospinal tract axons. Atlastin-1, the protein encoded by ATL1, is one of three mammalian atlastins, which are homologous dynamin-like GTPases that control endoplasmic reticulum (ER) morphology by fusing tubules to form the three-way junctions that characterise ER networks. However, it is not clear whether atlastin-1 is required for correct ER morphology in human neurons and if so what the functional consequences of lack of atlastin-1 are. Using CRISPR-inhibition we generated human cortical neurons lacking atlastin-1. We demonstrate that ER morphology was altered in these neurons, with a reduced number of three-way junctions. Neurons lacking atlastin-1 had longer endosomal tubules, suggestive of defective tubule fission. This was accompanied by reduced lysosomal proteolytic capacity. As well as demonstrating that atlastin-1 is required for correct ER morphology in human neurons, our results indicate that lack of a classical ER-shaping protein such as atlastin-1 may cause altered endosomal tubulation and lysosomal proteolytic dysfunction. Furthermore, they strengthen the idea that defective lysosome function contributes to the pathogenesis of a broad group of HSPs, including those where the primary localisation of the protein involved is not at the endolysosomal system.

Decomposing PM2.5 concentrations in urban environments into meaningful factors 2. Extracting the contribution of traffic-related exhaust emissions.

Vehicle-emitted fine particulate matter (PM2.5) has been associated with significant health outcomes and environmental risks. This study estimates the contribution of traffic-related exhaust emissions (TREE) to observed PM2.5 using a novel factorization framework. Specifically, co-measured nitrogen oxides (NOx) concentrations served as a marker of vehicle-tailpipe emissions and were integrated into the optimization of a Non-negative Matrix Factorization (NMF) analysis to guide the factor extraction. The novel TREE-NMF approach was applied to long-term (2012-2019) PM2.5 observations from air quality monitoring (AQM) stations in two urban areas. The extracted TREE factor was evaluated against co-measured black carbon (BC) and PM2.5 species to which the TREE-NMF optimization was blind. The contribution of the TREE factor to the observed PM2.5 concentrations at an AQM station from the first location showed close agreement (R2=0.79) with monitored BC data. In the second location, a comparison of the extracted TREE factor with measurements at a nearby Surface PARTiculate mAtter Network (SPARTAN) station revealed moderate correlations with PM2.5 species commonly associated with fuel combustion, and a good linear regression fit with measured equivalent BC concentrations. The estimated concentrations of the TREE factor at the second location accounted for 7-11 % of the observed PM2.5 in the AQM stations. Moreover, analysis of specific days known to be characterized by little traffic emissions suggested that approximately 60-78 % of the traffic-related PM2.5 concentrations could be attributed to particulate traffic-exhaust emissions. The methodology applied in this study holds great potential in areas with limited monitoring of PM2.5 speciation, in particular BC, and its results could be valuable for both future environmental health research, regional radiative forcing estimates, and promulgation of tailored regulations for traffic-related air pollution abatement.

High Traffic Roads and Adverse Birth Outcomes: Comparing Births Upwind and Downwind of the Same Road.

Traffic related air pollution is a major concern for perinatal health. Determining causal associations, however, is difficult since high-traffic areas tend to correspond with lower socioeconomic neighborhoods and other environmental exposures. To overcome confounding, we compared pregnant individuals living downwind and upwind of the same high-traffic road. We leveraged vital statistics data for Texas from 2007-2016 (n=3,570,272 births) and computed hourly wind estimates for residential addresses within 500 m of high-traffic roads (i.e., annual average daily traffic greater than 25,000) (10.9% of births). We matched pregnant individuals predominantly upwind to pregnant neighbors downwind of the same road segment (n=37,631 pairs). Living downwind was associated with an 11.6 gram (95% CI: -18.01, -5.21) decrease in term birth weight. No associations were observed with low term birth weight, preterm birth, or very preterm birth. In distance-stratified models, living downwind within 50 m was associated with a -36.3 gram (95% CI: -67.74, -4.93) decrease in term birth weight and living 51-100m downwind was associated with an odds ratio of 3.68 (95% CI: 1.71, 7.90) for very preterm birth. These results suggest traffic air pollution is associated with adverse birth outcomes, with steep distance decay gradients around major roads.

Navigating Road Traffic Accidents in Jordan: A Retrospective Exploration of the Health and Economic Impacts.

Background Road traffic accidents (RTAs) are considered a major public health threat. The causes of RTAs are multifactorial, comprising both human and non-human factors. RTAs may result not only in detrimental health consequences but also in serious economic burdens. This study aimed to provide a retrospective overview of the health and economic impacts of RTAs in Jordan during the period 2013-2021, including the implemented multisectoral mitigation strategies. Methodology This study presents a retrospective chart review of the traffic reports published by the Public Security Directorate (PSD) in Jordan during the period 2013-2021. The examined variables were the total number of road accidents involving human injuries per year, average road accidents per day, annual deaths, average deaths per day, deaths per 100,000 population, annual number of injuries, average number of injuries per day, severity of human injury, number of registered vehicles, and the annual financial costs. Data were extracted from PSD reports and presented descriptively. Results The number of registered vehicles has risen from 1,263,754 in 2013 to 1,795,215 in 2021 with a 42.1% increase. This was also associated with an increase in the average RTAs per day from 28.0 in 2013 to 30.8 in 2021. The total number of RTAs that involved human injuries during the period 2013-2021 fluctuated with 8,451 in 2020 (lowest) and 11,241 in 2021 (highest). In the same period, annual deaths caused by RTAs peaked in 2013 with 768 deaths (highest) compared to 461 in 2020 (lowest). In the five years from 2017 to 2021, the total financial cost of RTAs in Jordan was nearly 1.561 billion Jordanian Dinars (~2.2 billion U.S. dollars) compared to 1.363 billion Jordanian Dinars (~1.92 billion U.S. dollars) in the five years from 2012 to 2016. Conclusions Targeting human and road infrastructure factors through effective government-society partnerships is crucial in mitigating the health and economic burden of RTAs in Jordan. More strict enforcement of traffic laws, along with incremental increases in the penalties for dangerous traffic violations, and regular road safety campaigns are expected to provide more control over the human factors of RTAs. Further research is needed to evaluate the impact of the recently amended traffic law on the trends of RTAs in the country.

Traffic safety comprehensive evaluation of urban tunnel visual guiding system based on extension matter-element model: a case study in tunnel curves.

OBJECTIVE: The visual guiding system, as a tunnel traffic safety improvement method by using visual guiding facilities to actively guide driving safely, has been widely used in countries with many tunnels, in recent years. This paper aims to quantitatively study the comprehensive evaluation of traffic safety of the visual guiding system in tunnels, which has certain engineering application value and can provide support for the quantitative evaluation and optimal design of tunnel traffic safety. METHODS: Based on the analysis of the relevant factors of urban tunnel traffic safety, a multi-factor comprehensive evaluation system with 5 upper-level indicators and 12 basic-level indicators was proposed. Considering the independent and incompatible indicators, a comprehensive evaluation method of traffic safety of the visual guiding system in urban tunnels was constructed by using the extension matter-element model. Taking the scene of 4 types of tunnel curves, such as no facilities, horizontal stripe, chevron alignment sign, and LED arch, as examples, the comprehensive evaluation of various schemes were carried out by using simulation tests. RESULTS: The traffic safety comprehensive evaluation system of visual guiding system in urban tunnels can be analyzed from five aspects: perception reaction, guidance ability, driver factor, driving task, and facility appearance. The results demonstrated significant the comprehensive evaluation result of the target level of scene 1 was L4, scene 2 was L3, scene 3 was L2, and scene 4 was L1. That is, the final results of the comprehensive evaluation of the four scenes were poor, medium, good, and very good, respectively. CONCLUSIONS: In the scheme of visual guiding system for urban tunnel curves, the effectiveness of the three types of designs, from high to low, was the LED arch, chevron alignment sign, and horizontal stripe, and the safety of the scene without facilities was the lowest. Hence, setting the LED arch in the urban tunnel curve has a good effect in the aspects of guidance ability, sight distance, and sight zone, and is conducive to the driver's perception reaction and driving task.

Cost-utility analysis of an alcohol policy in Thailand: a case study of a random breath testing intervention.

BACKGROUND: Road traffic injuries are a major concern worldwide, with Thailand facing high accident mortality rates. Drunk driving is a key factor that requires countermeasures. Random breath testing (RBT) and mass media campaigns recommended by the World Health Organisation intend to deter such behaviour. This study aimed to evaluate the cost-effectiveness of implementing RBT in combination with mass media campaigns in Thailand. METHODS: A Markov simulation model estimated the lifetime cost and health benefits of RBT with mass media campaigns compared to mass media campaigns only. Direct medical and non-medical care costs were evaluated from a societal perspective. The health outcomes were quality-adjusted life years (QALY). Costs and outcomes were discounted by 3% per year. Subgroup analyses were conducted for both sexes, different age groups, and different drinking levels. Probabilistic sensitivity analyses were conducted over 5,000 independent iterations using a predetermined distribution for each parameter. RESULTS: This study suggested that RBT with mass media campaigns compared with mass media campaigns increases the lifetime cost by 24,486 THB per male binge drinker and 10,475 THB per female binge drinker (1 USD = 35 THB) and results in a QALY gain of 0.43 years per male binge drinker and 0.10 years per female binge drinker. The intervention yielded incremental cost-effectiveness ratios (ICERs) of 57,391 and 103,850 THB per QALY for male and female drinkers, respectively. Moreover, the intervention was cost-effective for all age groups and drinking levels. The intervention yielded the lowest ICER among male-dependent drinkers. Sensitivity analyses showed that at a willingness-to-pay (WTP) threshold of 160,000 per QALY gained, the RBT combined with mass media campaigns had a 99% probability of being optimal for male drinkers, whereas the probability for females was 91%. CONCLUSIONS: RBT and mass media campaigns in Thailand are cost-effective for all ages and drinking levels in both sexes. The intervention yielded the lowest ICER among male-dependent drinkers. Given the current Thai WTP threshold, sensitivity analyses showed that the intervention was more cost-effective for males than females.

Identifying emerging hot spots of road traffic injury severity using spatiotemporal methods: longitudinal analyses on major roads in Ghana from 2005 to 2020.

BACKGROUND: Although road traffic injuries and deaths have decreased globally, there is substantial national and sub-national heterogeneity, particularly in low- and middle-income countries (LMICs). Ghana is one of few countries in Africa collecting comprehensive, spatially detailed data on motor vehicle collisions (MVCs). This data is a critical step towards improving roadway safety, as accurate and reliable information is essential for devising targeted countermeasures. METHODS: Here, we analyze 16 years of police-report data using emerging hot spot analysis in ArcGIS to identify hot spots with trends of increasing injury severity (a weighted composite measure of MVCs, minor injuries, severe injuries, and deaths), and counts of injuries, severe injuries, and deaths along major roads in urban and rural areas of Ghana. RESULTS: We find injury severity index sums and minor injury counts are significantly decreasing over time in Ghana while severe injury and death counts are not, indicating the latter should be the focus for road safety efforts. We identify new, consecutive, intensifying, and persistent hot spots on 2.65% of urban roads and 4.37% of rural roads. Hot spots are intensifying in terms of severity and frequency on major roads in rural areas. CONCLUSIONS: A few key road sections, particularly in rural areas, show elevated levels of road traffic injury severity, warranting targeted interventions. Our method for evaluating spatiotemporal trends in MVC, road traffic injuries, and deaths in a LMIC includes sufficient detail for replication and adaptation in other countries, which is useful for targeting countermeasures and tracking progress.

Native desert plants have the potential for phytoremediation of phytotoxic metals in urban cities: implications for cities sustainability in arid environments.

Arid regions can benefit from using native desert plants, which require minimal freshwater and can aid in remediating soil phytotoxic metals (PTMs) from traffic emissions. In this study, we assessed the ability of three native desert plants-Pennisetum divisum, Tetraena qatarensis, and Brassica tournefortii-to accumulate phytotoxic metals (PTMs) in their different plant organs, including leaves, stems, and roots/rhizomes. The PTMs were analyzed in soil and plant samples collected from Dubai, United Arab Emirates (UAE). The results indicated significantly higher levels of PTMs on the soil surface than the subsurface layer. Brassica exhibited the highest concentrations of Fe and Zn, measuring 566.7 and 262.8 mg kg-1, respectively, while Tetraena accumulated the highest concentration of Sr (1676.9 mg kg-1) in their stems. In contrast, Pennisetum recorded the lowest concentration of Sr (21.0 mg kg-1), while Tetraena exhibited the lowest concentrations of Fe and Zn (22.5 and 30.1 mg kg-1) in their leaves. The roots of Pennisetum, Brassica, and Tetraena demonstrated the potential to accumulate Zn from the soil, with concentration factors (CF) of 1.75, 1.09, and 1.09, respectively. Moreover, Brassica exhibited the highest CF for Sr, measuring 2.34. Pennisetum, however, could not translocate PTMs from its rhizomes to other plant organs, as indicated by a translocation factor (TF) of 1. In contrast, Brassica effectively translocated the studied PTMs from its roots to the stem and leaves (except for Sr in the leaves). Furthermore, Pennisetum exclusively absorbed Zn from the soil into its leaves and stems, with an enrichment factor (EF) greater than 1. Brassica showed the ability to uptake the studied PTMs in its stem and leaves (except for Fe), while Tetraena primarily absorbed Sr and Zn into its stems. Based on the CF and TF results, Pennisetum appears to be a suitable species for phytostabilization of both Fe and Zn, while Brassica is well-suited for Sr and Zn polluted soils. Tetraena shows potential for Zn phytoremediation. These findings suggest that these plants are suitable for PTMs phytoextraction. Furthermore, based on the EF results, these plants can efficiently sequester PTMs.

ITC-Net-blend-60: a comprehensive dataset for robust network traffic classification in diverse environments.

OBJECTIVES: Recognition of mobile applications within encrypted network traffic holds considerable effects across multiple domains, encompassing network administration, security, and digital marketing. The creation of network traffic classifiers capable of adjusting to dynamic and unforeseeable real-world settings presents a tremendous challenge. Presently available datasets exclusively encompass traffic data obtained from a singular network environment, thereby restricting their utility in evaluating the robustness and compatibility of a given model. DATA DESCRIPTION: This dataset was gathered from 60 popular Android applications in five different network scenarios, with the intention of overcoming the limitations of previous datasets. The scenarios were the same in the applications set but differed in terms of Internet service provider (ISP), geographic location, device, application version, and individual users. The traffic was generated through real human interactions on physical devices for 3-15 min. The method used to capture the traffic did not require root privileges on mobile phones and filtered out any background traffic. In total, the collected dataset comprises over 48 million packets, 450K bidirectional flows, and 36 GB of data.