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Selecting an appropriate intensity of epidemic prevention and control measures is of vital significance to promoting the two-way dynamic coordination of epidemic prevention and control and economic development. In order to balance epidemic control and economic development and suggest scientific and reasonable traffic control measures, this paper proposes a SEIQR model considering population migration and the propagation characteristics of the exposed and the asymptomatic, based on the data of COVID-19 cases, Baidu Migration, and the tourist economy. Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. With Xi'an City as an example. The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. With the continuous rise of traffic control intensity in different simulation scenarios, the cumulative number of cases decreases by a significant amplitude. While balancing the requirements for epidemic prevention and control and for tourist economy development, the model works out the control intensity to be 0.68, under which some traffic control measures are suggested. The model presented in this paper can be used to analyze the impacts of different traffic control intensities on epidemic transmission. The research results in this paper reveal the traffic control measures balancing the requirements for epidemic prevention and control and for economic development. [ABSTRACT FROM AUTHOR]

The article presents the problem of the cargo transport with the example of a selected mode of transport in Poland. The volume of goods transported by air transport in 2010-2021 was analysed. Cargo transport in air transport is very popular. From year to year, there is an increase in the volume of transported goods. The coronavirus pandemic, and the related economic crisis did not significantly affect cargo transport, as was the case with passenger transport, the number of which decreased significantly during the pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has shown to be a global challenge that, in addition to other effects, has influenced travel behavior. This study examines factors affecting academic travelers' mode choice before and during the pandemic and factors contributing to sustainable transportation on campus. By examining their travel patterns and behaviors, we contribute to understanding transportation preferences and identifying opportunities for sustainable transportation on university campuses. Studying academic travelers is crucial as they are significant daily travelers with a substantial impact on transportation systems and the environment. Understanding their mode choices helps transportation planners and policymakers promote sustainable transportation options. The literature has identified influential factors in making trips to university campuses, including age, gender, accommodation, cost, and travel time. However, cross-sectional studies involving comprehensive variables are lacking and the influence of the COVID-19 pandemic on transportation has not been thoroughly evaluated. To address this gap, the current study aims to evaluate novel variables, including intra-transport modes, entry permits, accessibility, parking availability, occupations, level of study, travel purpose, and visit frequency. The University of Isfahan, accessible by all modes of transport, was selected as the study area. After analyzing the questionnaire and variables using SPSS software (IBM SPSS Statistics for Windows, Version 22.0 Released 2013), travel behavior was studied by discrete choice models and the models' coefficients were estimated using NLOGIT. The finding demonstrated that using private modes (taxi, private vehicle, and active modes) increased in response to the pandemic, while using public modes (bus or subway) represented a decline. Before and during the pandemic, most people who had the same trip purpose shifted from taking the bus to using private vehicles and active transportation. Generally, people became more inclined to walk on campus during the pandemic. This study aimed to examine the travel behavior of academic travelers, who possess diverse travel choices compared with typical commuters, thus providing valuable insights into how the broader population might respond to different transportation options. The findings offer a novel perspective for university and city planners, enabling more informed decisions regarding sustainable development in campus areas. [ABSTRACT FROM AUTHOR]

The latest epidemic of COVID‐19 has significantly impacted both human capital and the global economy, contributing to pandemics and severe global crises. Research into the creation and propagation of the disease is desperately needed. The Internet of Things, cloud computing, and artificial intelligence offer modern technology for real‐time processing for multiple applications such as healthcare applications, transport, traffic control, and so on blockchain is an evolving technology that will dramatically boost transaction protection in finance, supply chain, and other transaction networks. A stable and latency‐sensitive Quality of Service framework for COVID‐19 is the need of an hour. The purpose of this paper is to combine Fog computing and Artificial Intelligence with smart health to establish a reliable platform for early‐stage detection of COVID‐19 infection. A new ensemble‐based classifier is proposed to detect COVID‐19 patients. This research offers a blockchain platform to analyse how the unrelated cases of the COVID‐19 virus can be tracked and identified using peer‐to‐peer, time stamping, and the shared storage advantages of blockchain. In addition to growing patient loyalty, this would effectively enhance the consistency, flexibility, productivity, performance, and effectiveness of healthcare services. The idea of blockchain is used to establish security for the whole framework. Different implementations measure the efficiency of the suggested system. The performance of the proposed framework is evaluated in terms of delay, network usages, RAM usages, and energy consumption. On the other hand, the classifier is evaluated in terms of classifier accuracy, recall, precision, kappa static, and root mean square error. The result shows the performance of the proposed framework and classifier is always better than the traditional frameworks and classifiers. [ABSTRACT FROM AUTHOR]

The rapid global spread of the coronavirus disease 2019 (COVID-19) is now a reality. China has taken urban traffic control measures to prevent and control the epidemic, but this has prevented the flow of people between cities. This study investigates the mechanism of the impact of urban traffic control measures on the intercity population flow in China using the one-way causal measurement method. The results show that the impact of urban traffic control measures on the intercity flow of the population changes with time. Based on this, this study makes scientific suggestions for the government on how to reasonably undertake traffic control measures. [ABSTRACT FROM AUTHOR]

With the spread of the COVID-19 pandemic and the implementation of closure measures in 2020, population mobility and human activities have decreased, which has seriously impacted atmospheric quality. Huaibei City is an important coal and chemical production base in East China, which faces increasing environmental problems. The impact of anthropogenic activities on air quality in this area was investigated by comparing the COVID-19 lockdown in 2020 with the normal situation in 2021. Tropospheric NO2, HCHO and SO2 column densities were observed by ground-based multiple axis differential optical absorption spectroscopy (MAX-DOAS). In situ measurements for PM2.5, NO2, SO2 and O3 were also taken. The observation period was divided into four phases, the pre-lockdown period, phase 1 lockdown, phase 2 lockdown and the post-lockdown period. Ground-based MAX-DOAS results showed that tropospheric NO2, HCHO and SO2 column densities increased by 41, 14 and 14%, respectively, during phase 1 in 2021 vs. 2020. In situ results showed that NO2 and SO2 increased by 59 and 11%, respectively, during phase 1 in 2021 vs. 2020, but PM2.5 and O3 decreased by 15 and 17%, respectively. In the phase 2 period, due to the partial lifting of control measures, the concentration of pollutants did not significantly change. The weekly MAX-DOAS results showed that there was no obvious weekend effect of pollutants in the Huaibei area, and NO2, HCHO and SO2 had obvious diurnal variation characteristics. In addition, the relationship between the column densities and wind speed and direction in 2020 and 2021 was studied. The results showed that, in the absence of traffic control in 2021, elevated sources in the Eastern part of the city emitted large amounts of NO2. The observed ratios of HCHO to NO2 suggested that tropospheric ozone production involved NOX-limited scenarios. The correlation analysis between HCHO and different gases showed that HCHO mainly originated from primary emission sources related to SO2. [ABSTRACT FROM AUTHOR]

In intelligent transportation, various types of sensors are used both in traffic control systems as well as in the control, safety, and entertainment systems of the vehicles themselves. In the process of educating future designers and developers of such systems, it is necessary to familiarize them with the operation and parameters of sensors. The recent years of the COVID-19 pandemic have disturbed this process due to the need to conduct classes remotely. This article presents the general concept of a laboratory stand for testing sensors of electrical and non-electrical quantities, which can be used both in stationary and remote learning. Additionally, the practical implementation of two laboratory stands for testing current and linear displacement sensors was also presented. Both stands have been tested in the remote access mode. The tests showed some shortcomings in the management software but also confirmed the correctness of the adopted concept of their implementation. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic large numbers of single-use, surgical style face masks were lost or discarded in public spaces, primarily in on public streets and car parking settings. Many of these masks were blown onto the road surfaces where they were subjected to degradation through the tire impact of passing vehicle traffic. As series of field observations as well as experimental simulations show that the three-ply polypropylene mask fabric is subjected to shear forces when compressed between the tire and the road surface. The mechanical action breaks the bonds between the fibers (both spunbonded and meltblown) leading to a continual shedding of microfibers. Wind disperses these into the environment along road sides, while surface water action moves them into stormwater drains and from there into the waterways. As the decay is rapid, municipal agencies only have a short window of time to remove stray face masks from the urban environment if micro-fiber pollution is to be reduced. [ABSTRACT FROM AUTHOR]

Since the beginning of the coronavirus pandemic in 2020, the transport sector has faced new challenges connected with decreasing use of public transport and passengers' concerns about possible contagion. Using focus groups and data collection by telephone interviews during the different phases of the pandemic, we investigated passengers' current concerns connected with public transport and what measures would help alleviate their fear of using it again. Our findings show that the pandemic has amplified passengers' sensitivity to phenomena they perceived negatively already before the pandemic, such as overcrowded vehicles, odours, or inadequate cleaning of vehicles. An appeal to people's own responsibility, appropriate communication by key institutions, increasing sanitation standards and promotion of contactless services are crucial for a safe travel feeling during and after the pandemic. The technological solutions, such as cashless payments, real-timeinformation for adequate guidance of users, more sophisticated ventilation systems etc. gained even more significance during the COVID-19 pandemic. In spite of various measures taken in the PT system, users reduced their PT trips substantially. The fear of COVID-19 contagion has been one of the reasons, although the fear of PT use has not been greater than the fear of contagion in other situations, such as shopping. One of the reasons for passengers´ decline was also the PT service reduction in frequency or number of connections. On the other hand, PT operators have been exposed to an enormous pressure to ensure sanitary requirements and had to overcome economic shortages due to a decreased demand and increased costs, so they had to find a viable balance between a necessary supply and safe operation during the COVID-19 waves. The study brings an overview of measures and changes in PT demand and gives a complex view on the development of attitudes and experience with PT use in the Czech Republic during the different phases of the COVID-19 pandemic. Results bring recommendations to PT providers, transport authorities and other institutions dealing with mobility and public health. Implementation of such measures can minimize the risk of contagion by COVID-19 or other respiratory infections and will help further development of public transport as a sustainable transport mode in the post-pandemic era. [ABSTRACT FROM AUTHOR]

Monitoring road traffic is extremely important given the possibilities it opens up in terms of studying the behavior of road users, road design and planning problems, as well as because it can be used to predict future traffic. Especially on highways that connect beaches and larger urban areas, traffic is characterized by having peaks that are highly dependent on weather conditions and rest periods. This paper describes a dataset of mobility patterns of a coastal area in Aveiro region, Portugal, fully covered with traffic classification radars, over a two-year period. The sensing infrastructure was deployed in the scope of the PASMO project, an open living lab for co-operative intelligent transportation systems. The data gathered includes the speed of the detected objects, their position, and their type (heavy vehicle, light vehicle, two-wheeler, and pedestrian). The dataset includes 74,305 records, corresponding to the aggregation of road information at 10 min intervals. A brief analysis of the dataset shows the highly dynamic nature of traffic during the two-year period. In addition, the existence of meteorological records from nearby stations, and the recording of daily data on COVID-19 infections, make it possible to cross-reference information and study the influence of weather conditions and infections on traffic behavior. [ABSTRACT FROM AUTHOR]

India is a fast Developing Country in the World. During Construction or development of Road Projects occurs a Accidents for Labours, Traffic Vehicles in sometime Environmental problems are created due to Unscientific or Unsafe Highway Construction Management Technique's. In the Highway Construction involves Physical, Chemical, Electrical, and Machineries Hazardous to the labours or Workers in Road Construction Site. And also includes Risky Operations and Occupational Unhealthy Operation, Unskilled labours Causes Deaths, Minor or Major Health issues, Accidents, delay of work, Cost affect to Contractors, losses of Construction Company Reputation. For the most important the Ergonomic injuries due to the High or Low illumination of light, High levels of Sound (db) Toxic Substances are causes the Accidents are occurred from the Ergonomic factors, Such as Exertion, Physical Contact with Pressure, Exposure to vibrating Machineries, Expose the body to Extreme Heat or Cold Environment have create major problems on Work and Safety of the Road Construction. Mainly the workers or Labors Suffering from the Muscular Skeletal Disorders, Strain & Stress Due to the hard work, Collision with Equipment, Vehicle related Accidents. Mainly the Labours and workers behavior Plays a very important role in the Road or Highway Construction Site. The Occupational Safety and Health Act (1970) defines Protect the Employers, have a legal obligation provide with a Safe Environment with Safety Precautionary Measurements in Highway Construction. The main agenda of this Paper is to Educate and Awareness for the labors, how and why to use of Personal Protective Equipment (PPE) at Highway Construction Site, Safety Regulations, Traffic Control Systems, Safety Culture adopted in Highway Construction, Identifying the Hazard Materials, First Aid Treatment, Causes of Accidents and Hazards, Environmental Awareness and Health Awareness Programs, Covid-19 Pandemic's etc. And Mainly the Paper Concluded that Create a Awareness among Highway Construction Workers and Educate to Adopt the Various Safety Related Equipments, Measurements, and Protection in Highway Construction Site. [ABSTRACT FROM AUTHOR]

Cities world-wide have taken the opportunity presented by the COVID-19 pandemic to improve and expand pedestrian infrastructure, providing residents with a sense of relief and pursuing long-standing goals to decrease automobile dependence and increase walkability. So far, due to a scarcity of data and methodological shortcomings, these efforts have lacked the system-level view of treating sidewalks as a network. Here, we leverage sidewalk data from ten cities in three continents, to first analyse the distribution of sidewalk and roadbed geometries, and find that cities present an unbalanced distribution of public space, favouring automobiles at the expense of pedestrians. Next, we connect these geometries to build a sidewalk network –adjacent, but irreducible to the road network. Finally, we compare a no-intervention scenario with a shared-effort heuristic, in relation to the performance of sidewalk infrastructures to guarantee physical distancing. The heuristic prevents the sidewalk connectivity breakdown, while preserving the road network's functionality. While public space is traditionally shared by pedestrian and cars, the distancing measures imposed by the Covid-19 pandemic have underlined the need for wider pedestrian spaces. Here, the authors take a complex network approach to analyze sidewalk data from cities across the world to evidence a strong unbalance in the space distribution between cars and pedestrian, and propose a strategy to improve urban walkability within a socially distancing context and without compromising road traffic. [ABSTRACT FROM AUTHOR]