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Although scholars have developed simulation models and analyzed bankability criteria in numerous papers to enhance the financial outcomes of Public-Private Partnerships (PPPs), the intersection between both fields considering alternatives to assess the financial impact of flexibility in both scope and financing, remains underdeveloped. To address this gap, this paper introduces a financial model that assesses the financial impact of suitable life-cycle flexibility alternatives while coexisting with revenue performance alterations in each project phase within toll road PPPs. This model serves as a tool to gain insight into the planning of strategic actions to implement flexibility in both scope and financing. Based on system dynamics and validated using financial data from two toll road PPPs in India and East Europe, simulation results suggest that two key drivers (capital expenditures and debt repayment period) have the greatest influence on financial performance. Findings support the implementation of flexible scopes to effectively address the most influential exogenous factor impacting the financial performance of PPPs, namely traffic shortfalls. This model provides a suitable tool for assessing the life-cycle economic sustainability of PPPs in uncertain and complex environments. [ABSTRACT FROM AUTHOR]

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]

In our study, we describe how the performance of certain modes of goods and passenger transport, as well as the postal service, has developed over the past hundred years, and how the stock of individual vehicles has changed. Technical development and methodological changes have significantly influenced the measurement and publication of certain areas of transport statistics. Based on the collection and processing of data from the Hungarian Statistical Yearbooks, we can state that natural metrics are capable of capturing long-term trends and well characterize the transport policy decisions of individual eras, as well as economic business cycles. [ABSTRACT FROM AUTHOR]

There is no intervention that quickly reduces a person's blood alcohol content (BAC). "Sober up before you drive" may prevent road traffic injury (RTI) caused by alcohol consumption. The aim of this study was to analyze the risk of RTI on an hourly basis (1–6 h) after the last drink and the determinants of this risk. This was a case-crossover study of alcohol consumption among 430 patients who suffered an RTI and arrived at an emergency department in a large hospital in Mexico City from January to April 2022. Of the 430 patients studied, 46 reported drinking within 1 h before the RTI, for a risk ratio (RR) of 7.7 (95% CI [5.6, 10.4]). This RR decreased to 2.2 (95% CI [1.3, 3.7]) for the 12 patients drinking in the second hour before the RTI and was null for those drinking earlier (p ≤ 0.001 for the trend). The induction time was 3 h among those with higher BAC and intoxication levels. The RR for an RTI decreases 71% from the first to second hour from the last drink and 32% from the second to third hour. This decrease was similar among those intoxicated and those with increased BACs. In multiple regression models, higher levels of intoxication and higher BACs remained associated with higher RRs. People should avoid driving after drinking. Waiting to drive, walking, or riding after drinking reduces the risk of an RTI, especially for people with higher BAC and intoxication levels. • The risk of TRI was higher 1 h after the last drink and decreased thereafter. • Risk was similar for drivers, pedestrians, and passengers. • The induction time was 1–2 h, extended for those with high BAC or intoxication. • Elevated risk depended on BAC at hospital entry and feeling intoxicated at injury. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco 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.)

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]

The consequences of sustainable and greener mobility have been demonstrated previous year by the pandemic situation. One significant benefit was to reduce the level of noise, dust and air pollution from the traffic in many European countries due to reduced mobility most of the population. Positive phenomena was also recorded in the Slovak Republic. Today's urban mobility offers new, more sustainable ways of transport for residents, especially app-based and shared-ride services, which have become increasingly widespread and very popular. Undoubtedly offer a level of convenience unseen before in the urban mobility systems throughout the world. Although new forms of transport are developed in most Slovak cities, their operation is not very rational and therefore individual car transport still dominates at the expense of sustainable ways of transport. In our paper, we analyze the traffic situation in the city of Nitra, as the large number of trips in the course of the peak-hours often results in severe traffic congestion. Multimodality is one of the solutions to improve the current traffic situation, as it allows urban residents to choose from a range of alternative travel options. The main aim of this paper is to determinate the possibilities of multimodal urban mobility in the city of Nitra in addition to analyze how the potential change in the variability of choice of means of transport affects the urban mobility behaviour. In order to meet stated objectives, a marketing research was conducted. The research findings point to the fact that the current urban infrastructure and overall possibilities are limited, the consequence of which is that travel behaviour of citizens does not demonstrate the features of sustainable urban mobility. Our results point to major differences in attitudes of Nitra´s residents from different urban and sub-urban areas. [ABSTRACT FROM AUTHOR]

This paper bridges the gap between the literature on the pandemic's effects on mobility and the literature on the impact of low emission zones (LEZ). Using data for large European cities in the period 2018–2021, we examine whether LEZs may explain differences in the recovery patterns of traffic in European cities after the shock of Covid. Controlling for several city attributes, we examine whether LEZ cities are less congested before and after the pandemic in comparison to non-LEZ cities. LEZs may have been more effective in reducing congestion after the pandemic because the fleet renewal process has slowed down or, alternatively, LEZs may be a proxy of unobservable factors related with attitudes of governments and citizens toward a sustainable mobility. Our results validate the traffic-mitigating role of the LEZ after the Covid-19 pandemic, although such result only holds for the pioneering LEZ cities. Hence, the traffic-mitigating role of the LEZ after the Covid-19 pandemic seems to be related to unobservable attributes that influenced the early decision to implement a LEZ. In this regard, we also find that LEZs may have induced a change in local attributes related to sustainable mobility given that we do not find differences between LEZs decided at the local or regional level. [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]

Counter-terrorism measures and preparedness play a critical role in securing mass gatherings, soft targets, and critical infrastructures within urban environments. This paper introduces a comprehensive Decision Support System developed as part of the S4AllCitites project, designed to seamlessly integrate with existing legacy systems in Smart Cities. The system encompasses urban pedestrian and vehicular evacuation, incorporating predictive models to anticipate the progression of incendiary and mass shooting attacks, alongside a probabilistic model for threat assessment in the case of improvised explosive devices. A notable achievement of this research is the successful implementation and deployment of the system in operational environments through pilot studies. It empowers public and private security operators with real time decision support capabilities during both prevention and intervention stages of potential attacks. The decision support information provided encompasses various aspects, including optimal evacuation strategies, estimated egress times, pedestrian movement profiles, probability assessments, and the potential impact of different terrorist threats in terms of casualties. Additionally, the system offers real-time insights into the status of the traffic network under normal and unusual conditions, enabling efficient emergency management throughout its progression. This includes the ability to identify optimal intervention routes and assess the impact of anomalous traffic resulting from evacuations. [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.