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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. [ABSTRACT FROM AUTHOR]

The intensive use, development, and expansion of the road network is expanding the zones of direct impact of road transport on forest ecosystems. Issues related to the mobility of trace elements in forest ecosystems along motorways are very important due to the numerous environmental risks associated with the excessive accumulation of metals, the ability to migrate and accumulate in plants and animals, and the risk of transferring these elements to higher trophic levels. The aim of this article was therefore to determine the impact of road traffic on the basis of contents of trace metals Cd, Cr, Cu, Ni, Pb, and Zn and to describe the relationship of these contents in moss gametophytes and blueberry leaves taken in the vicinity of an existing and variously expanded expressway (S7, Poland, Europe). Analyses of transport impacts included the effects of distance and time of pollutant deposition and road transport on habitat and stand conditions. The highest contents of Cd, Cr, Cu, Ni, Pb, and Zn in moss tissues were found in fir stands and the contents were, respectively, 0.36 mg·kg−1, 5.91 mg·kg−1, 12.5 mg·kg−1, 3.26 mg·kg−1, 8.82 mg·kg−1, and 55.28 mg·kg−1. Mosses showed the best bioindication capacity of all of the studied ecosystem elements. The Pb, Zn, Cr, Cu, and Ni contents were particularly markedly elevated in moss tissues relative to non-anthropopressured areas and dependent on distance from the emitter (road). Blueberry proved to be a less useful bioindicator, as the contents of Cd, Cr, Cu, Ni, Pb, and Zn found were similar to the data from non-anthropopressured areas and were, respectively, 0.09 mg·kg−1, 0.98 mg·kg−1, 7.12 mg·kg−1, 2.49 mg·kg−1, 1.18 mg·kg−1, and 15.91 mg·kg−1 in fir stands and 0.04 mg·kg−1, 0.47 mg·kg−1, 6.63 mg·kg−1, 1.65 mg·kg−1, 0.72 mg·kg−1, and 17.44 mg·kg−1 in pine stands. [ABSTRACT FROM AUTHOR]

Objective. To estimate the prevalence of non-fatal road traffic injuries (RTIs), their characteristics, trend and consequences in the Mexican population. Materials and methods. A descriptive study using data from the National Health and Nutrition Survey (Ensanut Continua 2021-2023), designed with probabilistic, multistage, and stratified sampling. The prevalence of RTIs by sex, age group, region, residence area, well-being index, and type of road user was estimated, as the proportion of use of protective measures and health consequences. Results. The prevalence of non-fatal RTIs was 1.31% (95%CI: 1.1,1.5), approximately 1.6 million individuals, of whom more than 90% required medical attention and 28.4% reported a permanent health consequence. They were more frequent in urban areas and the regions of Estado de México and Peninsula (79.1, 15.1, and 14.1%, respectively), in males (71.1%), and in motorcycle users. Conclusions. The increase in the prevalence of nonfatal RTIs and the persistence of risky road safety behaviors underline the urgency of strengthening public policies and their implementation. [ABSTRACT FROM AUTHOR]

Childhood asthma is a major health issue in Australia, and traffic emissions play a causative role. Two urban planning policies that impact children's exposure to traffic emissions are considered in terms of the potential health risks to children in a Melbourne suburb with high truck volumes and hospital attendances for childhood asthma. Firstly, the health impact assessment component of the state planning approval of a major road project, and secondly, local government placement of childcare centres and schools in relation to freight routes. Three sources of air quality monitoring data were examined: (i) a Victorian EPA reference site; (ii) a site with planning approval for development into a childcare centre; and (iii) five sites within the boundary of the West Gate Tunnel Project, an AUD 10 billion road and tunnel project. The Australian Urban Research Infrastructure Network data was utilised to assess distances of childcare centres and schools from major truck routes. A range of cconcentration–response functions for childhood asthma (0–18 years) from international systematic meta-analyses and a smaller Australian cross-sectional study were applied to comparative elevations in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations between the EPA reference monitor (used for project risk assessment) and local roadside data. It was found that comparative elevations in NO2 concentrations were associated with the following risk increases: developing asthma 13%, active asthma 12%, and lifetime asthma 9%. Overall, 41% of childcare centres (n = 51) and 36% of schools (n = 22) were ≤150 m to a high-density truck route. Truck emissions likely make a substantial contribution to childhood asthma outcomes in the project area. This study exemplifies how current practices may not be commensurate with guiding policy objectives of harm minimisation and equitable protection. [ABSTRACT FROM AUTHOR]

Traffic management is a critical activity, the population is increasing day by day and so the traffic on the road is also increasing. Traffic jams and long waiting queues of vehicles at the road crossing are now part of everyone's life. The traffic lights used at the crossing to regulate the traffic play a vital role in the smooth functioning of traffic movement. At a crossing of four roads, it has been observed that giving an equal amount of green light to all roads is meaningless since the arrival of traffic on different paths is different. Importantly, the arrival rate is responsible for all traffic jams, long queues, and increased waiting time. Therefore, this paper suggests a green light allocation scheme for all paths i depending on the arrival rate of the vehicles. Thus, the allocation of green light will be dynamic. Further, weight is also computed, where more arrival rate means more weight, thereby assigning more time to the green signal. This will help in reducing the long queue length, residual traffic, and long waiting times. On simulating the traffic with the traffic data, the proposed optimized green light allocation scheme to path i reduces the residue traffic to negligible, allowing smooth traffic flow even during peak hours. The work also provides a proficient optimization of the waiting time of vehicles accumulated during the red light. According to the simulation, the maximum time assigned for the green signal during the peak hour of 9:30 AM to 10:00 AM for paths i , where 1 ≤ i ≤ 4 is 39.96, 33.36, 26.64, and 20.04 seconds respectively. Similarly, during the second rush hour of 5:00 PM to 6:00 PM, the simulation assigns a green signal time of 41.4, 37.2, 24.84, and 16.56 seconds for corresponding paths 1–4. Thus, the proposed work suggests an effective traffic management scheme at the four-road crossing. [ABSTRACT FROM AUTHOR]

Road traffic accidents pose a global challenge with substantial human and economic costs. Iran experiences a high incidence of road traffic injuries, leading to a significant burden on society. This study aims to predict the future burden of road traffic injuries in Iran until 2030, providing valuable insights for policy-making and interventions to improve road safety and reduce the associated human and economic costs. This analytical study utilized time series models, specifically autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs), to predict the burden of road traffic accidents by analyzing past data to identify patterns and trends in Iran until 2030. The required data related to prevalence, death, and disability-adjusted life years (DALYs) rates were collected from the Institute for Health Metrics and Evaluation database and analyzed using R software and relevant modeling and statistical analysis packages. Both prediction models, ARIMA and ANNs indicate that the prevalence rates (per 100,000) of all road traffic injuries, except for motorcyclist road injuries which have an almost flat trend, remaining at around 430, increase by 2030. Based on estimations of both models, the rates of death and DALYs due to motor vehicle and pedestrian road traffic injuries decrease. For motor vehicle road injuries, estimated trends decrease to approximately 520 DALYs and 10 deaths. Also, for pedestrian road injuries these rates reached approximately 300 DALYs and 6 deaths, according to the models. For cyclists and other road traffic injuries, the predicted DALY rates by the ANN model increase to almost 50 and 8, while predictions conducted by the ARIMA model show a static trend, remaining at 40 and approximately 6.5. Moreover, these rates for the prediction of death rate by the ANN model increased to 0.6 and 0.1, while predictions conducted by the ARIMA model show a static trend, remaining at 0.43 and 0.07. According to the ANN model, the predicted rates of DALY and death for motorcyclists decrease to 100 and approximately 2.7, respectively. On the other hand, predictions made by the ARIMA model show a static trend, with rates remaining at 200 and approximately 3.2, respectively. The prevalence of road traffic injuries is predicted to increase, while the death and DALY rates of road traffic injuries show different patterns. Effective intervention programs and safety measures are necessary to prevent and reduce road traffic accidents. Different interventions should be designed and implemented specifically for different groups of pedestrians, cyclists, motorcyclists, and motor vehicle drivers. [ABSTRACT FROM AUTHOR]

Increased daily exposure to fine particulate matter air pollution (PM2.5) is associated with increased morbidity, yet high exposures over shorter timeframes (e.g., hourly) may also play a role. Transportation is a milieu for increased transient pollution exposures. Both the road traveled and nearby roadways (i.e., surrounding road density) may play a role in increased PM2.5 exposure during commutes. For 2311 min of commutes, corresponding to 25 participants, we obtained in-vehicle PM2.5 exposures using personal monitors and, through GPS data, road features, including road density and road type (e.g., highway vs. local roads). We considered the density of both the surrounding highways and the local roads at 500 m and 1000 m resolutions. We estimated associations of road features with minute-averaged in-vehicle PM2.5 by applying linear mixed-effects models with random intercepts and autoregressive errors. The difference in log PM2.5, comparing the highest vs. lowest quartile of highway road density at 1 km resolution, was 0.09 log μg/m3 (95% confidence interval: 0, 0.19), which was similar to the difference between driving on highways vs. local roads (0.07 log μg/m3 (95% confidence interval: 0.00, 0.14)). Estimated differences were attenuated for local road density and 500 m resolution. The results were robust to adjustment for meteorology and ambient PM2.5. Unlike road features such as speed and road type, the surrounding road density is less modifiable during transportation. Therefore, road choice may not have a large impact on personal PM2.5 exposures. [ABSTRACT FROM AUTHOR]

Objectives: The noise intensity emitted by transportation vehicles in the city of Hit was measured, and for all the city's neighborhoods at specific points (5) m away from the noise source and for a period of (2) minutes. The measurement was made using a sound level meter (Edos\Ds-102). The measurement points were determined using the GPS system to determine locations.Methodology: The research relied on the descriptive and analytical-deductive approach as well as field work.Results: The noise was measured at the specified points (5) times and the average for these points was taken, by calculating the reading rate for the roads and streets of the city of Hit and measuring the noise intensity resulting from the various means of transportation and traffic in these streets. It was found that the highest noise intensity rate was recorded in Al-Jisr Street and its value reached (82dB) in the morning period as it is one of the important commercial streets and witnesses traffic congestion. As for the lowest reading rate, it was recorded in (Hit Hospital) Street and its value reached (64dB) in the evening. It is noted that the noise intensity measured by means of transportation in the study area is higher than the global and local determinants.Conclusion: The highest noise intensity rate was recorded in Al-Jisr Street and its value reached (82.4 dB) in the morning period as it is one of the important commercial streets that witnesses traffic congestion in the morning period, followed by Al-Jari Street with a measurement rate of (82 dB). The lowest reading rate was recorded in Hit Hospital Street, with a value of (64dB) in the evening. It is noted that the noise intensity measured by means of transportation in the study area is higher than the global and local standards. Map (2) shows the distribution of road and means of transportation noise in the city of Hit.

The transportation sector wields substantial influence on society, encompassing economic, social and environmental dimensions of sustainability. Recognising environmentally conscious actions initiated by individuals, particularly at grassroots levels, fosters the development of a pro-environmental social identity. The article aims to analyse the transportation systems from a bottom-up perspective within a municipality. Consequently, three objectives are proposed for this research paper: investigate citizen behaviour regarding transportation, assess the strengths and weaknesses of communities based on citizen perspectives and generate ideas for improving transit through responsible management principles using a bottom-up approach. It has been determined that private car is the most commonly used mode of transportation. The number of cars is the only variable that influences the choice of transportation. A significant positive relationship has been identified between the number of cars and car travels, while a negative relationship has been observed between the number of cars and travels by transit, pedestrian or bicycle. In addition to this, other significant relationships were determined. Regarding the second objective, the majority of the interviewees perceive that the commune lacks any significant strengths. In terms of enhancement opportunities, respondents express a desire for improvements in pedestrian and cyclist infrastructure, transit facilities and the addition of more lanes and roads.

Safety is a global concern affecting learners to and from schools. The negative effects on learners are physical and psychological and could lead to disability, depression, and decline in learner performance. Scholars are entitled to a safe schooling climate that is free from endangering their lives. The main objective of this paper was to explore safety issues faced by scholar patrols in their attempt to safeguard scholar pedestrians on their way to and from schools. A qualitative approach with a case study design was employed to provide an understanding of the threat to safety as experienced by scholar patrollers. Participants in this paper comprised educators, parents, and Grade six learners of the two former Model-C schools in the Potgietersrus circuit in Limpopo Province. Data from interviews and a document review were the data collection methods. Data collected was analysed through thematic content analysis. Research results indicated that the safety and security of scholar patrollers are receiving increasing attention. Also, the scholar patrol comprises two teams that relieve each other on an alternatively scheduled basis, scholar patrol is a call for unselfish services by fellow pupils to their communities hence the programme of scholar patrollers provides safer access to primary schools at nearby crossings. Based on the shared research results, it was recommended that all stakeholders such as educators, parents, and scholar patrollers should continue to take scholar patrolling seriously since it serves to safeguard fellow learners. The study on scholar patrolling will contribute to teaching about road safety and encourage learners to observe the rules of safety.

Purpose: Road traffic accidents pose a global challenge with substantial human and economic costs. Iran experiences a high incidence of road traffic injuries, leading to a significant burden on society. This study aims to predict the future burden of road traffic injuries in Iran until 2030, providing valuable insights for policy-making and interventions to improve road safety and reduce the associated human and economic costs. Methods: This analytical study utilized time series models, specifically autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs), to predict the burden of road traffic accidents by analyzing past data to identify patterns and trends in Iran until 2030. The required data related to prevalence, death, and disability-adjusted life years (DALYs) rates were collected from the Institute for Health Metrics and Evaluation database and analyzed using R software and relevant modeling and statistical analysis packages. Results: Both prediction models, ARIMA and ANNs indicate that the prevalence rates (per 100,000) of all road traffic injuries, except for motorcyclist road injuries which have an almost flat trend, remaining at around 430, increase by 2030. Based on estimations of both models, the rates of death and DALYs due to motor vehicle and pedestrian road traffic injuries decrease. For motor vehicle road injuries, estimated trends decrease to approximately 520 DALYs and 10 deaths. Also, for pedestrian road injuries these rates reached approximately 300 DALYs and 6 deaths, according to the models. For cyclists and other road traffic injuries, the predicted DALY rates by the ANN model increase to almost 50 and 8, while predictions conducted by the ARIMA model show a static trend, remaining at 40 and approximately 6.5. Moreover, these rates for the prediction of death rate by the ANN model increased to 0.6 and 0.1, while predictions conducted by the ARIMA model show a static trend, remaining at 0.43 and 0.07. According to the ANN model, the predicted rates of DALY and death for motorcyclists decrease to 100 and approximately 2.7, respectively. On the other hand, predictions made by the ARIMA model show a static trend, with rates remaining at 200 and approximately 3.2, respectively. Conclusion: The prevalence of road traffic injuries is predicted to increase, while the death and DALY rates of road traffic injuries show different patterns. Effective intervention programs and safety measures are necessary to prevent and reduce road traffic accidents. Different interventions should be designed and implemented specifically for different groups of pedestrians, cyclists, motorcyclists, and motor vehicle drivers.

Traffic management is a critical activity, the population is increasing day by day and so the traffic on the road is also increasing. Traffic jams and long waiting queues of vehicles at the road crossing are now part of everyone's life. The traffic lights used at the crossing to regulate the traffic play a vital role in the smooth functioning of traffic movement. At a crossing of four roads, it has been observed that giving an equal amount of green light to all roads is meaningless since the arrival of traffic on different paths is different. Importantly, the arrival rate is responsible for all traffic jams, long queues, and increased waiting time. Therefore, this paper suggests a green light allocation scheme for all paths i depending on the arrival rate of the vehicles. Thus, the allocation of green light will be dynamic. Further, weight is also computed, where more arrival rate means more weight, thereby assigning more time to the green signal. This will help in reducing the long queue length, residual traffic, and long waiting times. On simulating the traffic with the traffic data, the proposed optimized green light allocation scheme to path i reduces the residue traffic to negligible, allowing smooth traffic flow even during peak hours. The work also provides a proficient optimization of the waiting time of vehicles accumulated during the red light. According to the simulation, the maximum time assigned for the green signal during the peak hour of 9:30 AM to 10:00 AM for paths i, where 1≤i≤4 is 39.96, 33.36, 26.64, and 20.04 seconds respectively. Similarly, during the second rush hour of 5:00 PM to 6:00 PM, the simulation assigns a green signal time of 41.4, 37.2, 24.84, and 16.56 seconds for corresponding paths 1–4. Thus, the proposed work suggests an effective traffic management scheme at the four-road crossing.

Inhaled particles and gases can harm health by promoting chronic inflammation in the body. Few studies have investigated the relationship between outdoor air pollution and inflammation by race and ethnicity, socioeconomic status, and lifestyle risk factors. We examined associations of particulate matter (PM) and other markers of traffic-related air pollution with circulating levels of C-reactive protein (CRP), a biomarker of systemic inflammation. CRP was measured from blood samples obtained in 1994-2016 from 7,860 California residents participating in the Multiethnic Cohort (MEC) Study. Exposure to PM (aerodynamic diameter ≤2.5 μm [PM2.5], ≤10 μm [PM10], and between 2.5 and 10 μm [PM10-2.5]), nitrogen oxides (NOx, including nitrogen dioxide [NO2]), carbon monoxide (CO), ground-level ozone (O3), and benzene averaged over one or twelve months before blood draw were estimated based on participants' addresses. Percent change in geometric mean CRP levels and 95% confidence intervals (CI) per standard concentration increase of each pollutant were estimated using multivariable generalized linear regression. Among 4,305 females (55%) and 3,555 males (45%) (mean age 68.1 [SD 7.5] years at blood draw), CRP levels increased with 12-month exposure to PM10 (11.0%, 95% CI: 4.2%, 18.2% per 10 μg/m3), PM10-2.5 (12.4%, 95% CI: 1.4%, 24.5% per 10 μg/m3), NOx (10.4%, 95% CI: 2.2%, 19.2% per 50 ppb), and benzene (2.9%, 95% CI: 1.1%, 4.6% per 1 ppb). In subgroup analyses, these associations were observed in Latino participants, those who lived in low socioeconomic neighborhoods, overweight or obese participants, and never or former smokers. No consistent patterns were found for 1-month pollutant exposures. This investigation identified associations of primarily traffic-related air pollutants, including PM, NOx, and benzene, with CRP in a multiethnic population. The diversity of the MEC across demographic, socioeconomic, and lifestyle factors allowed us to explore the generalizability of the effects of air pollution on inflammation across subgroups.

BACKGROUND: Motor vehicle crashes among teen drivers often involve passengers in the teens vehicle and occupants of other vehicles, and the full cost burden for all individuals is largely unknown. This analysis estimated direct hospitalisation and emergency department charges for teen-involved crashes by teen culpability, comparing charges for the teen driver, passengers and occupants of other vehicles. METHODS: Probabilistic linkage was performed to link the Iowa police crash reports with Iowa emergency department and Iowa hospital inpatient data. Teen drivers aged 14-17 involved in a crash from 2016 through 2020 were included. Teen culpability was determined through the crash report and examined by teen and crash characteristics. Direct medical charges were estimated from charges through linkage to the Iowa hospital inpatient and the Iowa emergency department databases. RESULTS: Among the 28 062 teen drivers involved in vehicle crashes in Iowa between 2016 and 2020, 62.1% were culpable and 37.9% were not culpable. For all parties involved, the inpatient charges were $20.5 million in culpable crashes and $7.2 million in non-culpable crashes. The emergency department charges were $18.7 million in teen culpable crashes and $6.8 million in teen non-culpable crashes. Of the $20.5 million total inpatient charges in which a teen driver was culpable, charges of $9.5 million (46.3%) were for the injured teen driver and $11.0 million (53.7%) for other involved parties. CONCLUSIONS: Culpable teen-involved crashes lead to higher proportions of injury and higher medical charges, with most of these charges covering other individuals in the crash.

The authors consider the features of multi-agent modeling for traffic optimization in the central areas of cities. While evaluating the unique challenges associated with the high concentration of vehicles, pedestrians and historical buildings, the potential of multi-agent systems to effectively solve the problem of congestion, safety and quality of life in urban areas is investigated. The potential of multi-agent modeling in the context of traffic management in the central areas of the city allows us to identify the key challenges and opportunities. Many scientists address the main aspects of such modeling and use them in the transport and road sectors. A review of current research and development has shown that multi-agent models aim to simulate and optimize the supervision and control of transportation in various traffic scenarios. Modeling traffic organization in the central areas of cities is one of the main elements of urban development planning and management. Due to the growing population of cities and the increasing number of vehicles, the problems of congestion, air pollution, and inefficient use of infrastructure are becoming increasingly relevant. Therefore, it can be noted that multi-agent traffic modeling opens up new prospects for developing effective traffic management strategies, providing a flexible and adaptive solution to these problems. The research analyzes the existing approaches, identifies the system`s key components, and develops a model that demonstrates the interaction between agents and the environment based on a mathematical description. A practical simulation of the model, carried out using the AnyLogic software on the example of Lesia Ukrainka Boulevard in Kyiv, confirms the effectiveness of the multi-agent approach. The results of the study indicate the possibility of applying the developed model to improve intelligent information systems for traffic flow management, which opens up new prospects for improving traffic in the central areas of cities.

Background. Red-light violations (RLV) cause thousands of injuries and fatalities annually. All red lights are when all the traffic lights are red and require the evacuation of the intersection. In Iran, drivers disregard their approach’s signals, leading to serious front-to-side collisions. This study examined the violation relationship with traffic parameters and presented strategies for preventing front-to-side crashes at signalized intersections. Methods. Field data from 11 signalized intersections in Tabriz with a total of 27 approaches and various traffic and geometric characteristics were used for this study in order to determine factors influencing all RLVs. Results. The findings indicated that the risk of all RLVs increased with the red-light time variable in each approach. In addition, the risk of all RLVs was greater when the width of the approach and the number of vehicles in the first queue were lower. The variable of the left-turn type was also significant in the model and demonstrated that if the left-turn type is permitted, the risk of all RLVs would be higher. Conclusion. The results of this study can be used to prioritize the installation of cameras for crossing the stop line during red lights at intersections. Practical Implications. The location of adjacent traffic lights and pedestrian signal lights should be designed in such a way that they are not in the direct view of drivers and that they do not follow the changes in the adjacent approach traffic lights and start moving when the approach light turns green.

Abstract Higher concentrations of air pollutants, such as nitrogen dioxide (NO $$_\text {2}$$ 2 ) and particulate matter (PM), are observed in streets compared to the urban background. These concentrations could be predominantly attributed to road traffic, which remains an important source despite relentless efforts. In this study, performed over the Paris area, the impacts of the evolution of the fleet composition on urban air quality down to the street scale is assessed with two scenarios assuming the introduction of very-low-emission vehicles. Exhaust emission factors for these vehicles are based on the improvement of engine and after-treatment technologies, leading to factors lower than those proposed for the European emission standard Euro 7. Using the year 2014 as the baseline, very-low-emission vehicles are introduced up to the year 2030 for the Paris region. NO $$_\text {2}$$ 2 emissions are thus reduced by 68 % in streets, and concentrations by 53 %. However, PM concentration reduction is limited to 18 % in streets as non-exhaust emissions from tyre and brake wear and road abrasion are preponderant. PM emissions from non-exhaust sources represent 59 % of the total road-traffic emission of PM in 2014 and 89 % in 2030. Non-regulated pollutant concentrations are also reduced, by 42 % for black carbon and 30 % for organic matter. Considering only very-low-emission and electric vehicles in the fleet further reduce NO $$_\text {2}$$ 2 emissions and concentrations by 99.5 % and 80 % respectively. PM concentrations are only reduced by 22 %. This study highlights the high reduction potential of NO $$_\text {2}$$ 2 concentrations with very-low-emission and electric vehicles, because of reduction of exhaust emissions. However, difficulties remain to reduce PM concentrations in urban areas, with the large majority of PM traffic emissions coming from non-exhaust sources.

Introduction: Air pollution, largely driven by transportation emissions, poses significant health risks, including respiratory diseases, for individuals worldwide. Traffic police officers, who face prolonged exposure to vehicular emissions, are particularly vulnerable to respiratory morbidity. However, limited research exists on this topic, especially in regions like Hyderabad, India, known for poor air quality. This cross-sectional study aimed to investigate the prevalence and associated factors of respiratory morbidity among traffic police personnel in Hyderabad. Methods: A cross-sectional study was conducted from January 2021 to January 2023 among 258 traffic police personnel aged 25-58 years in Hyderabad. Data collection involved structured interviews using a questionnaire adapted from ATS DLD-78, lung function measurements via peak flow meter and spirometry, and assessment of environmental exposure using Air Quality Index data. Statistical analysis included descriptive statistics and logistic regression. Results: The study revealed a high prevalence of respiratory symptoms among traffic police personnel, with 32.5% reporting frequent respiratory complaints and 29.8% reporting chronic complaints. Lung function assessments indicated obstructive patterns in 28.7% of participants. Factors such as age over 35 years and exposure to areas with poor Air Quality Index showed statistically significant associations with respiratory morbidity. However, educational level, duration of exposure to traffic, smoking, and mask usage did not exhibit significant differences in respiratory morbidity. Conclusion: The study's findings underscore the increased risk of respiratory morbidity among traffic police officers due to prolonged exposure to vehicular emissions. Regular awareness sessions on personal protective equipment (PPE) and periodic health checkups are imperative to decrease health risks within this occupational group. Furthermore, rotating traffic police postings based on Air Quality Index rankings could help reduce exposure to pollutants and protect respiratory health. These interventions are crucial in addressing the significant burden of respiratory diseases among traffic police personnel in urban environments like Hyderabad.

Abstract Numerous efforts have been made to address the section‐level travel speed prediction problem. However, section‐level predictions can hardly be used for fine‐grained applications, such as lane management and lane‐level navigation. The main reason for this is that significant speed heterogeneity exists among the lanes within one section. Thus, this study proposes a three‐dimensional (3D) dual attention convolution‐based deep learning model for predicting the lane‐level travel speed. 3D convolutions are designed to learn high‐dimensional spatiotemporal traffic flow features, that is, the relationships between different sections, lanes, and periods. Dual attention modules are used to focus on the traffic flow propagation patterns and to explain the model's mechanisms. To evaluate the proposed model, an indicator is introduced to assess the spatio‐temporal learning ability, based on targeting the lane‐level case. Evaluation experiments are conducted based on loop detector data in Shanghai, China. The results show that high accuracy is obtained by the proposed model, with a 2.9 km/h mean absolute error, thereby outperforming several existing methods. Finally, an in‐depth analysis is provided regarding the attention coefficients and interpretation of real‐world lane‐level traffic flow propagation patterns, so as to gain insights into the model's mechanism when capturing dynamic lane‐level traffic flow.

Higher concentrations of air pollutants, such as nitrogen dioxide (NO 2 ) and particulate matter (PM), are observed in streets compared to the urban background. These concentrations could be predominantly attributed to road traffic, which remains an important source despite relentless efforts. In this study, performed over the Paris area, the impacts of the evolution of the fleet composition on urban air quality down to the street scale is assessed with two scenarios assuming the introduction of very-low-emission vehicles. Exhaust emission factors for these vehicles are based on the improvement of engine and after-treatment technologies, leading to factors lower than those proposed for the European emission standard Euro 7. Using the year 2014 as the baseline, very-low-emission vehicles are introduced up to the year 2030 for the Paris region. NO 2 emissions are thus reduced by 68 % in streets, and concentrations by 53 %. However, PM concentration reduction is limited to 18 % in streets as non-exhaust emissions from tyre and brake wear and road abrasion are preponderant. PM emissions from non-exhaust sources represent 59 % of the total road-traffic emission of PM in 2014 and 89 % in 2030. Non-regulated pollutant concentrations are also reduced, by 42 % for black carbon and 30 % for organic matter. Considering only very-low-emission and electric vehicles in the fleet further reduce NO 2 emissions and concentrations by 99.5 % and 80 % respectively. PM concentrations are only reduced by 22 %. This study highlights the high reduction potential of NO 2 concentrations with very-low-emission and electric vehicles, because of reduction of exhaust emissions. However, difficulties remain to reduce PM concentrations in urban areas, with the large majority of PM traffic emissions coming from non-exhaust sources. [ABSTRACT FROM AUTHOR]

Seatbelts and airbags are safety devices designed to prevent road traffic injuries (RTI). They reduce fatal outcomes in patients with RTI; however, studies comparing the preventive effectiveness of these devices are limited. This study aimed to compare the effectiveness of these devices in reducing mortality of patients with RTI. This retrospective cohort study was conducted using the Emergency Department-based Injury In-depth Surveillance (EDIIS) registry between January 2011 and December 2020. All patients who sustained RTI in vehicles with <10 seats were eligible. The target population was categorized into four groups: seat belt use and airbag deployment, seatbelt use-only, airbag deployment-only and non-use. The primary and secondary outcomes were in-hospital mortality and intracranial injury. The adjusted odds ratios (AORs) (95% confidence intervals (CIs)) of safety device use for related outcomes were calculated using multivariate logistic regression analysis. Among the 82,262 patients, 13,929 (16.9%) were classified into the seat belt use and airbag deployment group; 47,123 (57.4%), seat belt use-only; 1820 (2.2%), airbag deployment-only; and, 19,300 (23.5%), non-use group. Compared to the seat belt use-only group, the AORs (95% CIs) for in-hospital mortality and intracranial injury were 1.70 (1.31–2.19) and 1.29 (1.13– 1.47) in the seat belt use and airbags deployment group and 10.24 (7.49–13.99) and 3.00 (2.42–3.72) in the airbags deployment-only group, respectively. Seat belt use had significant preventive effects on in-hospital mortality and intracranial injury. Airbag deployment individually had no additional protective effect on clinical outcomes. [ABSTRACT FROM AUTHOR]

Noise pollution is generally regarded as an exposure of people or wildlife to levels of sound that are annoying, stressful, or damaging to the organism. Humans are exposed to noise constantly, from barely audible levels to potentially painful and damaging levels. Cities and agglomerations are subjected to the environmental noise pollution in a greater extent, so the smaller towns and villages are usually neglected in such monitoring studies. The aim of the present study was to: 1) develop a system for continuous environmental noise monitoring; 2) test and validate the system in the urban area of Smolyan town, Bulgaria; 3) assess the level of noise pollution based on systematic measurements. A simple system for continuous environmental noise monitoring has been developed. The system uses budget noise meters, class 2 (verified to be effective enough), placed in special cells for protection from atmospheric influences. The analogue signal from the sound meters is digitized and processed by a microcontroller to obtain the equivalent noise levels. This data is transmitted through an Ethernet controller to ThingSpeak, an IoT application and API for storing and retrieving data using HTTP protocols. Data from the continuous monitoring proved the existence of a significant environmental noise pollution in Smolyan (both in the central part and residential areas), which was almost permanent during twenty-four hours and all year round. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background. Red-light violations (RLV) cause thousands of injuries and fatalities annually. All red lights are when all the traffic lights are red and require the evacuation of the intersection. In Iran, drivers disregard their approach’s signals, leading to serious front-to-side collisions. This study examined the violation relationship with traffic parameters and presented strategies for preventing front-toside crashes at signalized intersections. Methods. Field data from 11 signalized intersections in Tabriz with a total of 27 approaches and various traffic and geometric characteristics were used for this study in order to determine factors influencing all RLVs. Results. The findings indicated that the risk of all RLVs increased with the red-light time variable in each approach. In addition, the risk of all RLVs was greater when the width of the approach and the number of vehicles in the first queue were lower. The variable of the left-turn type was also significant in the model and demonstrated that if the left-turn type is permitted, the risk of all RLVs would be higher. Conclusion. The results of this study can be used to prioritize the installation of cameras for crossing the stop line during red lights at intersections. Practical Implications. The location of adjacent traffic lights and pedestrian signal lights should be designed in such a way that they are not in the direct view of drivers and that they do not follow the changes in the adjacent approach traffic lights and start moving when the approach light turns green. [ABSTRACT FROM AUTHOR]

Objective: Unusual clinical course. Background: Numerous countries, Vietnam included, have persistently high annual rates of traffic accidents. Despite concerted government efforts to reduce the annual traffic accident rate, the toll of fatalities and consequential injuries from these accidents rises each year. Various factors contribute to these incidents, notably including alcohol consumption while driving, inadequate awareness of traffic regulations, and substandard traffic infrastructure. However, an under-recognized risk in developing nations such as Vietnam is the prevalence of sleep disorders. Conditions such as obstructive sleep apnea syndrome and obesity hypoventilation syndrome, while prevalent, remain inadequately assessed and treated. These disorders represent significant yet largely unaddressed contributors to the heightened risk of traffic accidents. Case Report: We describe the case of a 55-year-old Vietnamese man hospitalized due to long-standing respiratory complications and profound daytime sleepiness. Over the past 2 years, the patient gained 10 kg. Consequently, he frequently experienced drowsiness, leading to 4 traffic accidents. Despite previous hospitalizations, this sleep disorder had gone undiagnosed and untreated. Diagnostic assessments confirmed concurrent obstructive sleep apnea and obesity hypoventilation syndrome through polysomnography and blood gas analyses. Treatment involving non-invasive positive airway pressure therapy notably alleviated symptoms and substantially improved his quality of life within a concise 3-month period. Conclusions: Obstructive sleep apnea and obesity hypoventilation syndrome are contributory factors to excessive daytime somnolence, significantly increasing vulnerability to traffic accidents. Regrettably, this critical intersection remains inadequately addressed. Addressing these concerns comprehensively through dedicated research initiatives should be imperative before considering the universal issuance of driver's licenses to all road users in Vietnam. [ABSTRACT FROM AUTHOR]

This study has two parts as determining traffic LOS and nanoscale analyses on the filters which can collect nanoparticle materials sourced by exhaust waste. Therefore, at first, determination of the traffic behaviour as the level of service (LOS) in Sıhhiye campus of Hacettepe University in Ankara was studied. Then, exhaust gas analysis by using facing masks was conducted for different parameters and these masks were used to collect and analyse exhaust on them. The parameters were determined as vehicle and fuel types, filter masks, sampling distances respect to exhaust source. The measurements and samplings were realized for the vehicles which are public cars and service minibuses which use different fuel types as petrol, eco-diesel and diesel. Additionally, 5 different filter types were used to analyse traffic behaviour as exhaust gas may affect human health. For this reason, different mask types with different specified parameters, which are using as face masks for health and a new type was prepared by Argiope lobata spider silk membrane, were also investigated in relation to the filtered exhaust gases. Measurements were made for three different distances as 30, 60 and 90 cm from exhaust pipe output and with a constant sampling time range of 3 min. Apart from the previously known microscopic and macroscopic analyses on exhaust gases, it was examined whether the exhaust outputs frequently spread nanoparticle waste or not by using SAXS analyses on samples. As a result of the study, relation with traffic conditions with clear transportation can be affirmed. Additionally, the study reported important outcomes, such as a new designed filter mask material, which prevents the nanoparticles waste material, the critical distance from the exhaust sources and the importance of different fuel usage. [ABSTRACT FROM AUTHOR]

Numerous efforts have been made to address the section‐level travel speed prediction problem. However, section‐level predictions can hardly be used for fine‐grained applications, such as lane management and lane‐level navigation. The main reason for this is that significant speed heterogeneity exists among the lanes within one section. Thus, this study proposes a three‐dimensional (3D) dual attention convolution‐based deep learning model for predicting the lane‐level travel speed. 3D convolutions are designed to learn high‐dimensional spatiotemporal traffic flow features, that is, the relationships between different sections, lanes, and periods. Dual attention modules are used to focus on the traffic flow propagation patterns and to explain the model's mechanisms. To evaluate the proposed model, an indicator is introduced to assess the spatio‐temporal learning ability, based on targeting the lane‐level case. Evaluation experiments are conducted based on loop detector data in Shanghai, China. The results show that high accuracy is obtained by the proposed model, with a 2.9 km/h mean absolute error, thereby outperforming several existing methods. Finally, an in‐depth analysis is provided regarding the attention coefficients and interpretation of real‐world lane‐level traffic flow propagation patterns, so as to gain insights into the model's mechanism when capturing dynamic lane‐level traffic flow. [ABSTRACT FROM AUTHOR]

Having a walkable built environment is important to encourage active school transport. The aim of this study was to measure the walkability of all Perth, Western Australia (WA) schools and investigate whether differences in walkability exist by school type, socioeconomic status (SES) and/or subregion. Geographic Information Systems technology was used to measure walkability (i.e., traffic exposure and pedestrian connectivity) surrounding all Perth schools (n = 651) in 2021. Walkability scores and their individual components were compared using odds ratios and one-way ANOVAs with post-hoc comparisons by school type (primary, secondary and K-12; government and non-government), school SES and subregion. The majority of Perth schools (73.8%) were below the WA Planning Commission’s target for a walkable catchment area. Neighbourhoods surrounding high SES schools were significantly more walkable than neighbourhoods surrounding medium and low SES schools (mean walkability scores: 12.4, 10.5, 10.1, respectively, p <.001). Neighbourhoods surrounding schools located in the Central subregion (mean 12.3) were significantly more walkable than neighbourhoods surrounding schools located in the North-West (mean 11.0, p =.024), South Metropolitan (mean 10.0, p <.001) and North-East (mean 8.4, p <.001) subregions. No significant differences in walkability index scores were found for school type. This study found a large proportion of Perth schools were surrounded by disconnected street networks and that neighbourhoods surrounding high SES schools were, on average, more walkable than neighbourhoods surrounding medium and low SES schools. The results highlight the importance of modifying the built environment to increase opportunities for active school transport, particularly in low and medium socio-economic areas. [ABSTRACT FROM AUTHOR]

Copyright of Revista Didasc@lia: Didáctica y Educación is the property of Universitaria de Las Tunas, Centro de Estudios de Didactica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Archives of Environmental Protection is the property of Polish Academy of Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forces generated by actin assembly assist membrane invagination during clathrin-mediated endocytosis (CME). The sequential recruitment of core endocytic proteins and regulatory proteins, and assembly of the actin network, are well documented in live cells and are highly conserved from yeasts to humans. However, understanding of CME protein self-organization, as well as the biochemical and mechanical principles that underlie actins role in CME, is lacking. Here, we show that supported lipid bilayers coated with purified yeast Wiskott Aldrich Syndrome Protein (WASP), an endocytic actin assembly regulator, and incubated in cytoplasmic yeast extracts, recruit downstream endocytic proteins and assemble actin networks. Time-lapse imaging of WASP-coated bilayers revealed sequential recruitment of proteins from different endocytic modules, faithfully replicating in vivo behavior. Reconstituted actin networks assemble in a WASP-dependent manner and deform lipid bilayers, as seen by electron microscopy. Time-lapse imaging revealed that vesicles are released from the lipid bilayers with a burst of actin assembly. Actin networks pushing on membranes have previously been reconstituted; here, we have reconstituted a biologically important variation of these actin networks that self-organize on bilayers and produce pulling forces sufficient to bud off membrane vesicles. We propose that actin-driven vesicle generation may represent an ancient evolutionary precursor to diverse vesicle forming processes adapted for a wide array of cellular environments and applications.

All-terrain vehicle (ATV) incidents are one of the leading causes of injuries and fatalities among youth in the agricultural industry. It has been hypothesized that many youth-related ATV incidents occur because children ride ATVs that do not fit their capabilities and are not following basic safe riding practices. In addition, various ATV safety guidelines regarding youth (e.g., CPSC, ANSI/SVIA, ASI) are inconsistent and may not align with state or local laws. To the best of our knowledge, no comprehensive studies have compared the physical and mental requirements for riding ATVs and the youth's capabilities to ride ATVs safely. Consequently, there are no scientific-based recommendations for age limitation, physical and mental capabilities, and safety requirements for youth to ride ATVs safely. Thus, there is a need to review the available sources related to youth safety and ATVs in the agricultural industry, identify the research voids, and recommend modifications to current ATV guidelines. This study conducted a systematic review of available ATV-related studies, standards, guidelines, and laws to establish better-informed minimum age, physical and mental capabilities, and safety requirements for youths to ride ATVs on the farm.

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.

STUDY OBJECTIVE: To derive and initially validate a brief bedside clinical decision support tool that identifies emergency department (ED) patients at high risk of substantial, persistent posttraumatic stress symptoms after a motor vehicle collision. METHODS: Derivation (n=1,282, 19 ED sites) and validation (n=282, 11 separate ED sites) data were obtained from adults prospectively enrolled in the Advancing Understanding of RecOvery afteR traumA study who were discharged from the ED after motor vehicle collision-related trauma. The primary outcome was substantial posttraumatic stress symptoms at 3 months (Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders-5 ≥38). Logistic regression derivation models were evaluated for discriminative ability using the area under the curve and the accuracy of predicted risk probabilities (Brier score). Candidate posttraumatic stress predictors assessed in these models (n=265) spanned a range of sociodemographic, baseline health, peritraumatic, and mechanistic domains. The final model selection was based on performance and ease of administration. RESULTS: Significant 3-month posttraumatic stress symptoms were common in the derivation (27%) and validation (26%) cohort. The area under the curve and Brier score of the final 8-question tool were 0.82 and 0.14 in the derivation cohort and 0.76 and 0.17 in the validation cohort. CONCLUSION: This simple 8-question tool demonstrates promise to risk-stratify individuals with substantial posttraumatic stress symptoms who are discharged to home after a motor vehicle collision. Both external validation of this instrument, and work to further develop more accurate tools, are needed. Such tools might benefit public health by enabling the conduct of preventive intervention trials and assisting the growing number of EDs that provide services to trauma survivors aimed at promoting psychological recovery.

IntroductionExtremity injuries are a leading cause of morbidity in low- and middle-income countries (LMICs), often resulting in marked short-term and long-term disabilities. Most of the existing knowledge on these injuries originates from hospital-based studies; however, poor access to health care in LMICs limits these data because of inherent selection bias. This subanalysis of a larger population-level cross-sectional study in the Southwest Region of Cameroon aims to determine patterns of limb injury, treatment-seeking behaviors, and predictors of disability.MethodsHouseholds were surveyed in 2017 on injuries and subsequent disability sustained over the previous 12 months using a three-stage cluster sampling framework. Subgroups were compared using the chi square, Fisher exact, analysis of variance, Wald, and Wilcoxon rank-sum tests. Logarithmic models were used to identify predictors of disability.ResultsOf 8,065 subjects, 335 persons (4.2%) sustained 363 isolated limb injuries. Over half of the isolated limb injuries (55.7%) were open wounds while 9.6% were fractures. Isolated limb injuries most commonly occurred in younger men and resulted from falls (24.3%) and road traffic injuries (23.5%). High rates of disability were reported, with 39% reporting difficulty with activities of daily living. Compared with individuals with other types of limb injuries, those with fractures were six times more likely to seek a traditional healer first for care (40% versus 6.7%), 5.3 times (95% CI, 1.21 to 23.42) more likely to have any level of disability after adjustment for injury mechanism, and 2.3 times more likely to have difficulty paying for food or rent (54.8% versus 23.7%).DiscussionMost traumatic injuries sustained in LMICs involve limb injuries and often result in high levels of disability that affect individuals during their most productive years. Improved access to care and injury control measures, such as road safety training and improvements to transportation and trauma response infrastructure, are needed to reduce these injuries.

The relationship between legacy media and social media has become a crucial topic in the discussions about new media. The debate intensified after Facebook announced a reduction in news posts in user timelines in 2018. In the era of the “Like economy”, social media holds significant economic value, prompting media outlets to adopt a “let’s try and see” approach to reach new audiences and increase their online advertising share. The present study, based on a large-scale survey of 50 publishers’ websites, Facebook pages, and Twitter accounts, deepens our understanding of the relationship between legacy and social media as indicators of audience feedback. Through the lens of network gatekeeping and reciprocal journalism theories, it contributes to the development of new evaluation tools that predict publishers’ website traffic based on social media metrics. Results show that Facebook and Twitter metrics can predict publishers’ website traffic indicators at a rate exceeding 60%. This study underscores the importance of social media metrics in evaluating media practices and the need to shift research toward specific indicators to understand the relationship between legacy and social media.

Meteorological disasters along highways significantly reduce road traffic efficiency. Low visibility caused by heavy fog is a severe meteorological disaster that greatly increases highway traffic accidents. Accurately predicting highway visibility and taking timely response measures can reduce the impact of meteorological disasters and improve traffic safety. We proposed an Attention-based BiLSTM-CNN (ABCNet) model, which synergized attention mechanisms with BiLSTM and CNN technologies to forecast atmospheric visibility more accurately. First, the Bi-LSTM module processed information both forward and backward, capturing intricate temporal dependencies in the model. Second, the multi-head attention mechanism following the Bi-LSTM distilled and prioritized salient features from multiple aspects of the sequence data. Third, the CNN module recognized local spatial features, and a singular attention mechanism refined the feature map after the CNN module, further enhancing the model's accuracy and predictive capability. Experiments showed that the model was accurate, effective, and significantly advanced compared to conventional models. It could fully extract the spatiotemporal characteristics of meteorological elements. The model was integrated into practical systems with positive results. Additionally, this study provides a self-collected meteorological dataset for highways in high-altitude mountainous areas.

Abstract Urban traffic demand forecasting is an important component in the implementation of intelligent transport systems (ITS). Urban traffic demand data is a spatiotemporal data, describing the amount of traffic demand generated by different areas or stations within a city along the time dimension. Although there has been considerable research work, researchers still face several challenges in predicting accurately, including the capture of hidden features in the temporal dimension of such spatiotemporal data, and the capture of dynamic dependent changes in the spatial dimension. These are even more difficult for long‐time series prediction tasks. This paper designs a multivariate temporal forecasting model specifically adapted to traffic demand to address these challenges, called the Gated Spatiotemporal Graph Attention Network (GSTGAT). GSTGAT is based on the Transformer framework and the whole model is used in an end‐to‐end manner. First of all, it uses the gated self‐attention to extract temporal features in the sequence. Secondly, graph attention is used to capture the spatial dependencies among different variables in the unstructured space. Finally, the use of gated recurrent units in combination with hidden spatial states is proposed to capture multiple levels of spatial dependencies. Experimental results on the taxi dataset in New York and the bicycle dataset in San Francisco Bay Area show that the authors’ proposed model outperforms other state‐of‐the‐art models and improves the prediction accuracy.

A crucial component of an interactive Virtual Reality (VR) experience is high-quality, real-time image rendering and display, which requires high-end hardware in VR headsets. Cloud VR offers a compelling alternative by offloading computationally intensive rendering tasks to remote servers. However, such a distributed operation requires a real-time reliable delivery of the VR traffic over the networks, which is a challenging task. Therefore, a thorough understanding of the VR traffic characteristics, Quality of Service (QoS) requirements, and the impact of packet service on the quality of VR is required. The paper provides insights in this area by exploring the traffic generated by a cloud VR application of an off-the-shelf Pico Neo 2 VR headset. Specifically, it identifies often-overlooked application features with a significant impact on QoS and develops a novel VR application model that accounts for these features. These findings are used in three ways. First, the paper shows that the 3GPP baseline underestimates the effective VR bitrate, i.e., the bandwidth needed to deliver VR traffic by 25%, while the developed model provides a much more accurate estimation. Second, the model is used to evaluate the benefits of intra-refresh video coding and adjusting video buffering at the VR headset according to motion-to-photon requirements. Finally, based on the revealed important features, the paper improves a VR bitrate adaptation algorithm.

Abstract Reinforced concrete (RC) bridge decks are directly exposed to daily traffic loads and often experience surface cracking caused by excessive stress or fatigue accumulation. The bridge deck fatigue performance over traffic loads needs to be assessed based on accurate dynamic interaction analysis of the bridge and realistic moving vehicles. Most of existing studies on fatigue assessment focus on either the bridge global response without sufficient details about the bridge deck, or refined bridge deck modeling without considering the full dynamic interaction between moving traffic and the bridge structure realistically. A hybrid fatigue assessment approach is developed by combining mode-based global bridge-traffic dynamic interaction analysis, finite-element (FE)-based refined bridge deck model, and fatigue assessment method directly based on the vehicle loads and shear strength of the bridge deck. The proposed approach is demonstrated with a typical 3-span concrete bridge under realistic traffic and road surface conditions. Based on the dynamic interaction and stress analysis results, the fatigue damage factor is further investigated with different road surface roughness levels and heavy truck proportions. It is found that the proposed analytical approach provides a useful tool to predict the bridge deck response and potential fatigue damage under realistic traffic flow.

In addition to traffic, the main source of nitrogen dioxide is also industrial plants where combustion takes place at high temperatures, such as heating plants and smelters. Nitrogen oxides from traffic are the dominant component of air pollution in large cities and represent an important source of exposure and health risk for people, especially those who move along busy roads. In Bor, real-time nitrogen dioxide concentrations have been measured since 2010 at the measuring point "Institute IRM Bor" near Mining and Metallurgy Institute Bor. This paper presents an analysis of the results of measuring nitrogen dioxide concentrations in Bor in the periods 2010-2013 and 2019-2023. Based on the analysis of nitrogen dioxide measurement results, it was established that in both periods there are seasonal changes (heating/non-heating season) in nitrogen dioxide concentrations. Nitrogen dioxide concentrations were on average 17% higher in the heating season than in the non-heating season. Also, in the period 2019-2023 the average concentration of nitrogen dioxide was 28.6 µg/m3 , which is about 18% more compared to the period 2010-2013 in which the average concentration of nitrogen dioxide was 24.3 µg/m3 . In the observed periods, there was no exceedance of the limit value for the average annual concentration of nitrogen dioxide of 40 µg/m3 . However, several days were recorded with an average daily concentration of nitrogen dioxide above the daily limit value of 85 µg/m3 .

The present article aims to bring to the attention of the public the compensations granted to people injured as a result of traffic accidents. In the lives of each of us, tragic events remind everyone of the importance of abiding by the traffic rules and paying more attention to the road both as drivers and as pedestrians. Car drivers are urged to be cautious, adapt speed to road conditions and avoid reckless behaviour in traffic. Also, pedestrians must know and respect the traffic rules. Practically, these are simple measures that make the difference between life and death, between a happy life and one in which traumas affect the state of well-being, of normality, in similar emergency situations.

ABSTRACTWe tackle the issue of how one might close the gap between geographies of people’s behavioural experiences and computer models designed to depict those geographies as simulations. We introduce the idea of Immersive Geosimulation Environments (IGEs) as a methodology for coupling spatial behaviour directly to simulation by providing access to (and interaction with) geographic information in ways that elicit user response as fully realized spatial spatial experiences. Importantly, IGEs allow spatial behaviour to be embodied to geosimulation, rather than remaining vicarious to its geography. To examine the utility of IGE methodology, we demonstrate a worked example in the safety science of road-crossing. We present an end-to-end IGE testbed for examining pedestrian – traffic – environment interactions at the roadside. The IGE is designed to achieve congruence between reality and simulation across two related channels. Congruence in fidelity tackles adherence to real-world counterparts, i.e. the condition that IGE elements should function with authenticity to real-world geographies. Congruence in verisimilitude addresses how realistic IGEs seem to the individual user experience, i.e. an IGE’s ability to evoke natural spatial behaviour within model scenarios. Our results point to the significance of embodiment in closing the reality gap. We posit that facilitating the formation of action maps, which relate models to users’ behaviour, could be key in providing functionally embodied geographic information systems and geosimulation systems.

Background: The incidence of traffic accidents in Iran is significantly higher than the global average (more than 17000 deaths a year, mostly young adults). The aim of this study was to determine the risk factors of high-risk drivers based on their observable driving behaviors, police records, and car condition in Fars province (Iran).Methods: In this case-control study, an interviewer interviewed a random sample (about 1 in 5 of the drivers) of all drivers who were referred to Shiraz traffic accident court from March 21, 2021, to June 21, 2021, due to being involved in a traffic accident. Based on the police report, we interviewed at-fault drivers who caused injurious or fatal traffic accidents as the case group (200 at-fault drivers) and those not-at-fault drivers as the control group (200 not-at-fault drivers). No matching was done. Data were collected using a researcher-made questionnaire filled out through face-to-face interviews with the drivers. Using univariate and multivariate logistic regression, the statistical analyses were conducted in R 4.0.2 software.Results: In this study, a total of 400 drivers were interviewed, of whom 367 (91.8%) were male. The mean ages of the case and control groups were 32.35 years (SD=9.84) and 31.75 (SD=10.33) years, respectively (P>0.05). In addition, 102 (51.0%) and 95 (47.5%) drivers were married in the case and control groups, respectively. Based on the results of a multiple logistic regression model, statistically significant associations were observed between the risk of being the at-fault driver in an injurious or fatal traffic accident and receiving a traffic ticket due to speedingovertaking (ORspeeding overtaking/no ticket=3.38, 95%CI: 1.75, 6.49, P

PROBLEM: It is unclear if attention-deficit hyperactivity disorder (ADHD) increases the risk of head trauma in children. METHODS: We conducted a multicenter prospective observational study of children with minor blunt head trauma. Guardians were queried, and medical records were reviewed as to whether the patient had previously been diagnosed with ADHD. Enrolled patients were categorized based on their mechanism of injury, with a comparison of those with motor vehicle collision (MVC) versus non-MVC mechanisms. FINDINGS: A total of 3410 (84%) enrolled children had ADHD status available, and 274 (8.0%; 95% confidence interval, CI: 7.1, 9.0%) had been diagnosed with ADHD. The mean age was 9.2 ± 3.5 years and 64% were males. Rates of ADHD for specific mechanisms of injury were: assaults: 23/131 (17.6%; 95% CI 11.5, 25.2%), automobile versus pedestrian 23/173 (13.3%; 95% CI: 8.6, 19.3%), bicycle crashes 26/148 (17.6%; 95% CI: 11.8, 24.7%), falls 107/1651 (6.5%; 95% 5.3, 7.8%), object struck head 31/421 (7.4%; 5.1, 10.3%), motorized vehicle crashes (e.g., motorcycle, motor scooter) 11/148 (7.4%; 3.8, 12.9%), and MVCs 46/704 (6.5%; 95% CI: 4.8, 8.6%). CONCLUSION: Children with ADHD appear to be at increased risk of head trauma from certain mechanisms of injury including assaults, auto versus pedestrian, and bicycle crashes but are not at an increased risk for falls.

ISSUES: Policy enforcement is crucial to achieve impacts on alcohol-related harm. It is not clear what level of enforcement intensity or dosage is necessary for addressing drink driving and related harms. Given competing enforcement demands and agencies resource constraints, understanding how much enforcement is sufficient to deter drink driving is critical. APPROACH: This systematic literature review followed Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) guidelines to examine research about dosage effects of enforcement and related visibility on drink-driving outcomes, including motor vehicle crashes and fatalities. Risk of bias was assessed using the Cochrane Collaboration Effective Practice and Organization of Care tool and the JBI checklist. KEY FINDINGS: The 21 studies that met the inclusion criteria for this review differed in measures of enforcement dosage and outcomes, making it difficult to synthesise results across studies and draw conclusions about a threshold or optimal level of enforcement. Although most included studies found that sustained enforcement was associated with reductions in drink driving or related harms, only two studies tested an optimal dosage. Due to study design limitations, a substantial percentage of these studies must be considered with caution. IMPLICATIONS: Additional research with rigorous study designs with appropriate controls is needed to determine an optimal high visibility enforcement dosage level to help law enforcement agencies make realistic decisions about allocating enforcement resources to address drink driving. CONCLUSION: Consistent evidence about a drink-driving enforcement dosage threshold is lacking, partly due to an insufficient number of well-designed studies. Addressing challenges of conducting rigorous studies in community settings is crucial.

PurposeAlcohol intoxication is a known risk factor for motor vehicle collisions. We hypothesize ethanol intoxication increases the risk of bladder injury and surgical repair, especially at higher blood alcohol content levels.Materials and methodsWe identified all patients involved in motor vehicle collisions from the National Trauma Data Bank from 2017-2019. Patients were categorized into an intoxication and intoxication negative group. Variables collected included age, sex, blood alcohol content level, driver status, seat belt restraint use, nonalcoholic intoxication, pelvic fracture, and Injury Severity Scale. Primary outcome measures of bladder injury and bladder surgical repair were assessed and interaction with pelvic fracture and restraint use were measured.ResultsWe identified 594,484 patients and 97,831 (16.5%) had a positive alcohol screen. Patients in the intoxication group were more likely to be intoxicated with other substances (32.8% vs 14.6%, P < .001), have a bladder injury (1% vs 0.4%, P < .001) and receive bladder surgical repair (0.7% vs 0.15%, P < .001). Injury Severity Scale and pelvic fracture were statistically significant predictors of bladder injury. In adjusted analysis, higher blood alcohol content was associated with both outcomes. Above the legal limit, alcohol intoxication was more predictive of bladder surgical repair than pelvic fracture. The association of alcohol intoxication with both outcomes did not differ by pelvic fracture, but strengthened with seat belt use at higher intoxication levels.ConclusionsAlcohol intoxication is independently associated with increased risk of bladder injury and subsequent bladder surgical repair following motor vehicle collisions. Trauma providers should have a high index of suspicion for bladder injuries in alcohol intoxicated patients, particularly those using seat belt restraints.

UNLABELLED: Obstructive sleep apnea (OSA) may lead to serious health, safety, and financial implications-including sleepiness-related crashes and incidents-in workers who perform safety-sensitive functions in the transportation industry. Evidence and expert consensus support its identification and treatment in high-risk commercial operators. An Advanced Notice of Proposed Rulemaking regarding the diagnosis and treatment of OSA in commercial truck and rail operators was issued by the Federal Motor Carrier Safety Administration and Federal Railroad Administration, but it was later withdrawn. This reversal has led to questions about whether efforts to identify and treat OSA are warranted. In the absence of clear directives, we urge key stakeholders, including clinicians and patients, to engage in a collaborative approach to address OSA by following, at a minimum, the 2016 guidelines issued by a Medical Review Board of the Federal Motor Carrier Safety Administration, alone or in combination with 2006 guidance by a joint task force. The current standard of care demands action to mitigate the serious health and safety risks of OSA. CITATION: Das AM, Chang JL, Berneking M, et al. Enhancing public health and safety by diagnosing and treating obstructive sleep apnea in the transportation industry: an American Academy of Sleep Medicine position statement. J Clin Sleep Med. 2022;18(10):2467-2470.

The decidual immunome is dynamic, dramatically changing its composition across gestation. Early pregnancy is dominated by decidual NK cells, with a shift towards T cells later in pregnancy. However, the degree, timing, and subsetspecific nature of leukocyte traffic between the decidua and systemic circulation during gestation remains poorly understood. Herein, we employed intravascular staining in pregnant C57BL/6J mice and cynomolgus macaques (Macaca fascicularis) to examine leukocyte traffic into the decidual basalis during pregnancy. Timed-mated or virgin mice were tail-vein injected with labelled αCD45 antibodies 24 hours and 5 minutes before sacrifice. Pregnant cynomolgus macaques (GD155) were infused with labelled αCD45 at 2 hours or 5 mins before necropsy. Decidual cells were isolated and resulting suspensions analyzed by flow cytometry. We found that the proportion of intravascular (IVAs)-negative leukocytes (cells labeled by the 24h infusion of αCD45 or unlabeled) decreased across murine gestation while recent immigrants (24h label only) increased in mid- to late-gestation. In the cynomolgus model our data confirmed differential labeling of decidual leukocytes by the infused antibody, with the 5 min infused animal having a higher proportion of IVAs+ cells compared to the 2hr infused animal. Decidual tissue sections from both macaques showed the presence of intravascularly labeled cells, either in proximity to blood vessels (5min infused animal) or deeper into decidual stroma (2hr infused animal). These results demonstrate the value of serial intravascular staining as a sensitive tool for defining decidual leukocyte traffic during pregnancy. [ABSTRACT FROM AUTHOR]

Short-term exposure to ultra-fine Black Carbon (BC) particles produced during incomplete fuel combustion of wood and fossil fuel has been linked to respiratory and cardiovascular diseases, hospitalizations and premature deaths. The goal of this research was to assess traffic-related BC in a cold climate along an urban highway and 300 m into an adjacent residential neighborhood. BC was measured with an aethalometer (MA350, Aethlabs) along the main traffic artery in geothermally heated Reykjavík, the capital of Iceland (64.135° N–21.895° W, 230,000 inhabitants). Stationary monitoring confirmed that traffic was the dominant source of roadside BC in winter, averaging 1.0 ± 1.1 µg/m3 (0.6 and 1.1 µg/m3 median and interquartile range; 28,000 vehicles/day). Inter-day variations in BC were primarily correlated to the atmospheric lapse rate and wind speed, both during stationary and mobile campaigns. During winter stills, BC levels surpassed 10 µg/m3 at intersections and built up to 5 µg/m3 during the afternoon in the residential neighborhood (adjacent to the highway with 43,000 vehicles/day). The BC penetrated deeply into the neighborhood, where the lowest concentration was 1.8 µg/m3 within 300 m. BC concentration was highly correlated to nitrogen dioxide (r > 0.8) monitored at the local Urban Traffic Monitoring site. [ABSTRACT FROM AUTHOR]