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Background: Road safety is a significant public health problem because it causes negative consequences on victims and families. The objective was to analyze the most significant changes in traffic crashes in Ecuador during the period from 2000 to 2019. With data obtained from the National Institute of Statistics and Census, we performed the analysis to identify: the number of traffic crashes, the number of victims, and other study variables. Methods: Descriptive and analytical statistics and the contrast of proportions were used to analyze data from 2000 to 2019. Results: According to the ideal joinpoint analysis model, there was a significant decrease in the number of recorded traffic accidents from 2015 to 2019 of −8.54 per year, while the tendency to die increased in females (2.05 per year) and males (3.29 per year). The most common crash was a collision, and the automobile appeared as the most involved vehicle from 2015 to 2019. The hypothesis test contrast is used to determine if statistically significant differences exist between age groups by gender of the driver injured in the period 2017–2018. Conclusions: This study determines the most significant changes in the variables related to traffic crashes, where mortality due to this cause in the last four years has had a growth rate of 1.8% compared to collisions that presented a rate of −31.12%. The contrast of the hypothesis test shows significant differences in the injury level between males and female drivers, depending on the age group.

Pine wilt disease (PWD) is regarded as one of the most serious conifer diseases affecting pines worldwide. To date, an in-depth study of the driving mechanisms behind short-distance PWD spread is lacking. In this study, we collected PWD forest subcompartment data in Fushun, China, and analysed the effects of factors on the short-distance transmission of PWD; the analysed factors included the number of neighbouring PWD-infected forest subcompartments, the canopy density, the slope direction, and different traffic corridor types. The results suggested that the spatial spill-over effect of nearby PWD-infected subcompartments contributed the most to short-distance PWD transmission, with an impact of up to 78% on its propagation. The impact of the traffic corridor was 20%. With the help of a beetle vector, PWD can spread to nearby forest subcompartments, and this spatial PWD spill-over effect showed a linearly decaying trend as the distance to neighbouring subcompartments increased. Different traffic corridor types exhibited significant PWD transmission impact differences. County roadways and highways had great impacts, while others had relatively small impacts. For each additional 100 m of distance from a county roadway, highway, national, or provincial roadway, the PWD infection risks in forest subcompartments were reduced by 18%, 11%, 5%, and 3%, respectively. In this study, we quantified the influence of driving factors on the short-distance spread of PWD and provided a theoretical basis for the control of PWD transmission; the results obtained herein are critical for maintaining the ecological security of forests, promoting ecological forest management and stabilising forest carbon sinks.

Road freight transport is indispensable to international economic cooperation and foreign trade. Across all continents, it is commonly used for short and medium distances and in long distance haulage when minimizing time is important. In all instances governments play a critical role in ensuring the competitive advantage of private sector operators. Countries often have many opportunities to minimize the physical or administrative barriers that increase costs, take measures to enhance the attractiveness and competitiveness of road transport, or generally nurture the integral role of international road freight transport in the global trade logistics industry. Road freight transport is critical to domestic and international trade. It is the dominant mode of transport for overland movement of trade traffic, carrying more than 80 percent of traffic in most regions. Generally, nearly all trade traffic is carried by road at some point. Therefore, the cost and quality of road transport services is of critical importance to trade competitiveness of countries and regions within countries. In fact, road transport is fundamental to modern international division of labor and supply-chain management.

In December 2019, the virus SARS-CoV-2 responsible for the COVID-19 pandemic was detected in the Chinese city of Wuhan. The virus started to spread from China and dispersed over the rest of the world. In March 2020, WHO (World Health Organization) declared COVID-19 a pandemic. The transmission path of the pandemic was accelerated by different types of transportation. With complete analysis of spatial data, population density, types of traffic networks, and their properties, the spatial distribution of COVID-19 was estimated. GIS (Geographical Information System), numerical methods, and software for network analysis were used in this research to model scenarios of virus distribution on a global scale. The analyzed data included air, railway, marine, and road traffic. In the pandemic research, numerous models of possible trajectory of viruses can be created. Many have a stochastic character. This study includes all countries in the world affected by the COVID-19 up to date. In this study, GIS methods such as buffer, interpolations, and numerical analysis were used in order to estimate and visualize ongoing COVID-19 pandemic situation. According to the availability of new data, trajectory of virus paths was estimated. On the other hand, sparsely populated areas with poorly developed and small traffic networks (and isolated island territories) tend to be less or not affected as shown by the model. This low-cost approach can be used in order to define important measures that need to be addressed and implemented in order to successfully mitigate the implications of COVID-19 not only on global, but local and regional scales as well.

In order to provide universal ability to access information and communication among Internet-connected devices, the Sustainable Internet of Things (IoT) is on a mission to bring all objects or devices under one roof. Future Internet architecture, especially Information-Centric Networking (ICN), can easily handle the connectivity offered and information created by the massive amount of devices to make it as sustainable IoT applications. Named Data Networking (NDN), one of the several future Internet designs that employ ICN as its foundation, shows promise. NDN integration with IoT-based applications gives solutions to numerous problems. However, this fusion makes accessing the IoT content easier, provided that an effective naming scheme is created to execute this operation. In this work, we build an innovative NDN-based naming scheme (NDN–NS) and put it into practise for consumer, producer, and content routers using our own secure forwarding schemes (NDN–NFS). Due to its scalability, heterogeneity, and security needs, IoT-based Smart Campus (IoT-SC) scenarios are taken into consideration for design and evaluation. We give a complete activity list based on NDN–NS that is split into two communication models (PusH Type Communication (PHTC) and PulL Type Communication (PLTC)) that can be applied to any IoT application. In terms of interest satisfaction rate (ISR), delay, and number of transmissions, we compare the NDN–NFS to legacy NDN. The outcomes demonstrate that NDN–NFS outperforms classic NDN in terms of performance and efficiency.

The steady rise in international trade volume has led to the high rate of utility of the marine industry. The gate system operation section of the marine terminal is a very pivotal aspect as it helps in the completion of the supply chain network. The drayage activities of pickups and delivery are single or double move operations at the terminal in order to meet customer's target. These operations are carried out by different types of trucks traffic: inbound and outbound trucks. This paper aims at investigating the flow pattern of these inbound and outbound trucks and their respective subdivision frequency at TICT in the year 2018. For the inbound trucks, 501-550 truck distribution had the highest interval with 34.5% as a daily percentage arrival within the operating hours. While with two-week interval, EMTIN (empty-in) dominated with a higher peak and CHIN had the least turn-out than the others inbound subdivisions. While for the outbound trucks pattern, it revealed that LDOUT (load-out) was domineering with a greater peak and the least was CHOUT (chassis-out). The rate of inbound to outbound truck volume for that year depicts the state of the countries dependency.

Little is known about the particles attached on the surfaces of coarse (> 150 μm) road-deposited sediments (RDS), which are potential contributors of stormwater pollution. Therefore, the size distributions and heavy metal (including Cu, Pb, Zn, Cr, and Ni) pollution of RDS were evaluated taking these attached particles into consideration. Moreover, the relationships of RDS contamination with traffic types were further discussed. The results showed that < 22, 22–38.5, 38.5–150, > 150 μm RDS and attached particles accounted for 2.1 ± 1.8%, 8.5 ± 5.7%, 50.7 ± 6.8%, 38.6 ± 8.3%, and 2.0 ± 1.2% of total RDS mass, respectively. The size distributions of attached particles were comparable to that of representative stormwater particles, suggesting their great potential to contribute stormwater particles by desorption. The Zn pollution of attached particles was remarkable, which was significantly higher than that of both fine (< 150 μm) and coarse (> 150 μm) RDS. The Cu and Pb pollution were comparable to that of fine RDS, which were significantly higher than that of coarse RDS. Conversely, the Cr and Ni pollution were comparable to that of coarse RDS, which were significantly lower than that of fine RDS. Traffic types were found to be closely related with RDS contamination, and thus are indicative of specific RDS pollution. For example, electrombile in old residential area is indicative of abnormal Pb pollution due to past emissions of leaded gasoline; lorry is indicative of remarkable Zn pollution of > 22 μm RDS due to abrasion of tires and metallic substances. Accordingly, traffic type is accessible to identify the typical pollutants in RDS to promote effective RDS management.

Type 2 diabetes mellitus (T2DM) is a growing public health problem in Bulgaria. While individual and lifestyle determinants have been researched; till date there has been no study on environmental risks such as road traffic, noise, and air pollution. As a first step toward designing a large-scale population-based survey, we aimed at exploring the overall associations of prevalent T2DM with exposures to road traffic, noise, and air pollution. A total of 513 residents of Plovdiv city, Bulgaria were recruited. Individual data on self-reported doctor-diagnosed T2DM and confounding factors were linked to objective and self-rated exposure indicators. Logistic and log-link Poisson regressions were conducted. In the fully adjusted logistic models, T2DM was positively associated with exposures to L den 71-80 dB (odds ratio (OR) = 4.49, 95% confidence interval (CI): 1.38, 14.68), fine particulate matter (PM) 2.5 25.0-66.8 μg/m 3 (OR = 1.32, 95% CI: 0.28, 6.24), benzo alpha pyrene 6.0-14.02 ng/m 3 (OR = 1.76, 95% CI: 0.52, 5.98) and high road traffic (OR = 1.40, 95% CI: 0.48, 4.07). L den remained a significant risk factor in the: Poisson regression model. Other covariates with consistently high multivariate effects were age, gender, body mass index, family history of T2DM, subjective sleep disturbance, and especially bedroom location. We concluded that residential noise exposure might be associated with elevated risk of prevalent T2DM. The inferences made by this research and the lessons learned from its limitations could guide the designing of a longitudinal epidemiological survey in Bulgaria.

Identifying road markings is a very important part of the vehicle environment sensing system and plays a crucial role in a vehicle’s correct understanding of a current traffic situation. However, road traffic markings are interfered with by a variety of factors, such as being obscured and the viewpoint of the vehicle sensors, resulting in large errors in the existing detection methods. In order to make the target detection task applicable to irregular objects or to detection tasks with higher accuracy requirements while reducing the waste of computational resources, this paper improves the accuracy of traffic marking segmentation detection by designing a multi-type traffic marking segmentation detection model based on image segmentation algorithms and designing a segmentation guidance matrix module based on a rank guidance matrix computation method. By constructing a comprehensive traffic marking detection model, a unified road traffic marking detection is achieved. Finally, the new traffic marking datasets ApolloScape-Precise and ApolloScape-Large are constructed based on the existing ApolloScape dataset, and experimental validation is carried out on these two datasets. The results show that the index MIoU (Mean Intersection over Union) of traffic marking segmentation detection reaches 61.44% and 70.15%, thus achieving a more perfect road traffic marking detection and right-of-way information perception and proving the effectiveness of the integrated traffic marking detection method designed in this paper.

Many concerns are arising now regarding the effects of the pollution on inhabitants, especially in agglomerated areas. It is known that mobility is a major factor that generates threatening pollution that negatively affects the health and the comfort of residents. The present study focuses on this sensitive subject by observing the impact of reducing mobility on air quality. There are various studies on this topic, but this analysis addresses a gap in the literature, by covering a very active area, in terms of development and attractiveness for new inhabitants. The research study was carried on Cluj-Napoca city (Romania), by measuring the concentration of SO2, NO2, O3, PM10, PM2.5 from five different air monitoring stations from Cluj County during 2019–2021. During the entire period, the concentrations of the measured pollutants regarding the air quality were far below the legally accepted limits, with some short time peaks generated by other human factors. Road vehicle traffic generates pollution, but they are not the only elements that have to be taken into consideration when the quality of life is regarded, so the lawmakers have a more complex task to comply when deliberating on this matter. It concludes that it is necessary to develop on the existing air quality measuring network stations, because it is necessary to increase the number and the quality of the measurements.