ABSTRACT
The COVID‐19 pandemic resulted in a widespread lockdown during the spring of 2020. Measurements collected on a light rail system in the Salt Lake Valley (SLV), combined with observations from the Utah Urban Carbon Dioxide Network observed a notable decrease in urban CO2 concentrations during the spring of 2020 relative to previous years. These decreases coincided with a ∼30% reduction in average traffic volume. CO2 measurements across the SLV were used within a Bayesian inverse model to spatially allocate anthropogenic emission reductions for the first COVID‐19 lockdown. The inverse model was first used to constrain anthropogenic emissions for the previous year (2019) to provide the best possible estimate of emissions for 2020, before accounting for emission reductions observed during the COVID‐19 lockdown. The posterior emissions for 2019 were then used as the prior emission estimate for the 2020 COVID‐19 lockdown analysis. Results from the inverse analysis suggest that the SLV observed a 20% decrease in afternoon CO2 emissions from March to April 2020 (−90.5 tC hr−1). The largest reductions in CO2 emissions were centered over the northern part of the valley (downtown Salt Lake City), near major roadways, and potentially at industrial point sources. These results demonstrate that CO2 monitoring networks can track reductions in CO2 emissions even in medium‐sized cities like Salt Lake City.Alternate :Plain Language SummaryHigh‐density measurements of CO2 were combined with a statistical model to estimate emission reductions across Salt Lake City during the COVID‐19 lockdown. Reduced traffic throughout the COVID‐19 lockdown was likely the primary driver behind lower CO2 emissions in Salt Lake City. There was also evidence that industrial‐based emission sources may of had an observable decrease in CO2 emissions during the lockdown. Finally, this analysis suggests that high‐density CO2 monitoring networks could be used to track progress toward decarbonization in the future.
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Aim - the discutability of existing scientific publications prompted a retrospective analysis of COVID-19 risk factors among the working population using the example of Russian Railways. Material and methods. Based on the archival documentation of medical institutions of Russian Railways, an analysis of the incidence of employees of the holding was carried out. Data from 2452 cases were analysed, for which full medical documentation was available. The comparison group randomly included 2911 workers who did not have COVID-19, comparable in sex, age, and area of residence. Results. Significant factors of difference between the groups of patients and those who were not ill were: sex, the presence of influenza vaccination, smoking and established diabetes mellitus. There was a trend towards an association of COVID-19 incidence and the presence of cardiovascular disease. In the comparison group, unlike the group of COVID-19 cases, there are 23% more persons who were vaccinated against influenza. In the group of patients with diabetes mellitus was found 3 times more often than in the group of non-patients. In both groups, the incidence rates of cardiovascular disease did not differ. However, as the severity of the disease increased, there was a tendency to increase the incidence of cardiovascular diseases. Meanwhile, the presence of other cardiovascular risk factors (male sex, smoking, diabetes mellitus, obesity) was significantly associated with a higher incidence in the disease group compared to non-patients. Multifactorial analysis also revealed other significant combinations of risk factors with COVID-19 risk: lack of influenza vaccination and the presence of diabetes mellitus;lack of vaccination, smoking and the presence of diabetes mellitus. Conclusion. For the working population, male sex and diabetes may be a significant risk factor for developing COVID-19. Influenza vaccination should be considered as a factor in anti- COVID-19 protection. Cardiovascular diseas e and smoking may serve as additional risk factors.Copyright © 2021 Infectious Diseases: News, Opinions, Training. All rights reserved.
ABSTRACT
Due to the interaction of electric multiple units (EMUs), and the electric traction networks, low frequency oscillations (LFOs) appear leading to traction blockade and overall stability related issues. For suppressing LFOs, coronavirus herd immunity optimiser (CHIO), a recently developed meta-heuristic, has been applied for tuning controller parameters. Controller parameters are tuned to minimise the integral time absolute error (ITAE) that regulates DC-link capacitor voltage. Results obtained using CHIO are compared with those found using other well-established algorithms like symbiotic organisms search (SOS) and particle swarm optimisation (PSO). The supremacy of CHIO over other mentioned algorithms for mitigating LFOs was demonstrated for a diverse range of operating conditions. Results demonstrates that overshoot for the proposed algorithm-based traction unit is 1.0061% whereas those for SOS and PSO based algorithm are obtained as 6.4542 % and 20.6166%, respectively which are quite high. CHIO is more stable than SOS and PSO and requires settling time of 0.1934 s only to reach steady-state condition, which is 50.21% faster than SOS and 65.03% faster than PSO. Also, the total harmonic distortion (THD) for line currents of the secondary side of traction transformer (TT) are obtained as 0.88%, 2.17%, and 12.48% for CHIO, SOS, and PSO, respectively.
ABSTRACT
Increasing the level of containerization in Russia is a source of competitiveness growth, since it focuses on increasing the efficiency of nationally oriented logistics and integration into global logistics chains, ensures transparency and productivity of the transport and logistics sector. The negative consequences caused by COVID-19 have affected freight transportation by all modes of transport. The reaction of carriers to the existing challenges largely determines the trajectory of development not only of railway container transportation, but also the format of the development of Russian cargo traffic for the coming years or even decades. The purpose of this study is to develop measures to increase the mobility of container cargo turnover on Russian railways and indicative designation of possible effects from their implementation. We prove that the development of infrastructure, stabilization of tariff policy, optimization of operational activities, expansion of the digital platform significantly affects the qualitative and quantitative development of rail container transportation based on mobility and logistics efficiency. The methodology of the study is based on the analysis of the target indicators of containerization of Russian railways for 2010–2020, the main product line of container transportation and competitors of the railway by means of transport. As a result of the study, trends in the growth of the share of container cargo turn-over on the Russian railway network are determined, the support of digital tools is justified in order to increase the mobility of container cargo turnover, a set of mechanisms for supporting and developing railway container transportation based on mobility and logistics efficiency is proposed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In light of the ongoing COVID-19 pandemic, it is important to analyse the ventilation system of an AC coach for safer as well as comfortable ride. In this study we have simulated the airflow, temperature distribution and velocity distribution inside the cabin, to find out the best layout for comfortable temperature as well as reduced chances of airborne infection. We have simulated various ventilation layouts of the 2 tier AC train coach of Indian Railways, to study the effect of the position of the inlet and outlet ports on the temperature and velocity distribution inside the cabin. CFD analysis was done using the Ansys Fluent solver employing the realizable k-ε model to solve the turbulence problem. Herein, a total of 12 layouts were simulated with 6 heated manikins sitting inside the cabin. The results of the study suggested that the temperature distribution inside the cabin changes significantly with a change in the inlet port position. Further, the layout with the above window and/or roof outlet has a relatively lower cabin temperature. This study forms the basis for further investigations to analyse the transmission of infection via cough droplets inside the cabin (unreported here). The results of this research are important for finding the optimum position of the inlet and outlet ports in AC coaches to enhance the overall thermal comfort and reduce infection transmission inside the cabin. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Relevance. The effectiveness of vaccination of the working population against COVID-19 in the Russian background has not been studied enough. Aim. To evaluate the effectiveness of vaccination of the working population with Gam-COVID-Vak (Sputnik V) in the Russian Railways as an example. Materials & Methods.The effectiveness of vaccination with Sputnik V among employees of Russian Railways in the period from January 21 to November 31, 2021 was performed with the Cox regression method. Results. The effectiveness of Sputnik V against COVID-19 infection with was 97.8% (95% CI 97.8–97.9%) for two doses, 91.9% (95% CI 91.6–92.2%) for a single dose, and 97.9% (95% CI 97.6–98.1%) for revaccination, all after socio-demographic factors adjusted. The effectiveness of vaccination against COVID-19 with hospitalization was 97.5% for two doses of Sputnik V (95% CI 97.1–97.9%), 86.1% (95% CI 83.7–88.1%) for a single dose, and 98.2% (95% CI 96.3–99.2%) for revaccination. The effectiveness against lethal COVID-19 was 95.2% (95% CI 93.1–96.6%) for two doses of Sputnik V and 94.8% (95% CI 89–97.6%) for one dose. The high efficiency of vaccination could be associated with a fairly young age composition of the employees of the Russian Railways. Conclusions. The study showed the high effectiveness of vaccination with Sputnik V against COVID-19 among the working population. © 2022, Numikom. All rights reserved.
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Europe experienced a dramatic and rapid drop of mobility in 2020 due to the COVID-19 pandemic during the different lockdowns periods. The impact was immediate and severe for long-distance travel in particular for the air transport industry. This crisis may also have long-term implications for the travel industry notably for business trips with the adoption of new ways of working. In this article, we point out the resilience of travel behaviors since we suggest that the pandemic is more likely to accelerate preexisting trends. Using time series data from Eurostat, we observe a preexisting decreasing trend for corporate travel. Data also suggest that flygskam is gaining Europe since 2018 with a slight reduction of air transport demand. These figures shed light on the near future of mobility in Europe. Leisure travel will be essential for operators’ recovery, opening up new business opportunities for rail transport (night trains, low-cost, etc.).
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Atmospheric particulate matter (PM10) is one of the most important pollutants for human health, and road transport could be a major anthropogenic source of it. Several research studies have shown the impact of roads on the air quality in urban areas, but the relationship between road and rail networks and ambient PM10 concentrations has not been well studied, especially in suburban and rural landscapes. In this study, we examined the link between the spatial characteristics of each road type (motorway, primary road, secondary road, and railway) and the annual average PM10 concentration. We used the European 2931 air quality (AQ) station dataset, which is classified into urban, suburban, and rural landscapes. Our results show that in urban and rural landscapes, the spatial characteristics (the density of the road network and its distance from the AQ monitoring points) have a significant statistical relationship with PM10 concentrations. According to our findings from AQ monitoring sites within the urban landscape, there is a significant negative relationship between the annual average PM10 concentration and the density of the railway network. This result can be explained by the driving wind generated by railway trains (mainly electric trains). Among the road network types, all road types in the urban landscape, only motorways in the suburban landscape, and only residential roads in the rural landscape have a significant positive statistical relationship with the PM10 values at the AQ monitoring points. Our results show that in the suburban zones, which represent the rural–urban fringe, motorways have a strong influence on PM-related air pollution. In the suburban areas, the speed of vehicles changes frequently near motorways and intersections, so higher traffic-related PM10 emission levels can be expected in these areas. The findings of this study can be used to decrease transportation-related environmental conflicts related to the air quality in urban, urban–rural fringe, and rural (agricultural) landscapes.
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The role of railways within urban areas is analysed, covering ‘metro’ systems (self-contained heavy rail networks, often with substantial underground sec-tions), light rail (both upgraded street tramways and newer systems), and travel by regional and national railways within urban areas. Basic operating characteristics, system capacity, capital costs, and technological change are examined. ‘Sustainability’ is analysed in respect of energy use and environmental impact, railways’ role in supporting high-density urban living (with associated benefits through greater use of non-motorised modes), and financial aspects (coverage of operating costs and ability to finance capital renewals). Current issues examined include the effect of users shifting to more flexible working patterns, the Covid pandemic, automation, and ownership. In general, urban railways can be seen to support a sustainable lifestyle, although some issues do arise in respect of longer distance commuting. © 2022 by Emerald Publishing Limited.
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Purpose>Public service motivation (PSM), among actual and prospective employees in the public sector, lead to positive work outcomes. However, there is limited integration of PSM with existing motivational theories, especially self-determination theory (SDT). The impact of destructive leadership styles on PSM is also understudied. The study aims to fill the gap.Design/methodology/approach>The study used a cross-sectional survey of 693 public sector officials employed in Indian Railways to test the hypotheses. PLS-SEM was used for the analysis. The study found that fulfillment of basic psychological needs (BPN) at work leads to improved PSM while BPN partially mediates the positive/negative effect of constructive/destructive leadership styles like servant/autocratic leadership on employees' PSM.Findings>Autocratic/servant leadership was negatively/positively and significantly related to PSM and to all three BPN needs. Servant leadership was found to be positively and significantly related to all three BPN needs, while the BPN needs partially mediated the relationship between servant leadership and PSM.Research limitations/implications>The study identifies servant leadership as a driver of PSM and suggests that managers employed in public sector establishments should be trained to be less autocratic and more attuned to subordinates' needs. The baneful impact of autocratic leadership on employee PSM is highlighted. The cross-sectional nature of study makes it susceptible to common-method bias. The sample was limited to a single country. Future longitudinal and experimental studies based on samples drawn from multiple countries can yield more robust results.Originality/value>The study advances the integration of PSM with SDT by identifying PSM with introjected motivation. It is also the first study to link destructive leadership styles with a reduction in employees' PSM. It identifies a counterintuitive, negative relationship between competence need satisfaction and PSM in the Indian public sector.
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The COVID-19 has led to people’s increased concern about health issues. In this paper, we investigate the needs of users traveling by high-speed rail in the post-pandemic era and optimize the design of high-speed rail seats, and evaluate the feasibility. Methodology: Using INPD combined with AHP and QFD to guide the design of high-speed railway seats, we use INPD as the main line of research and SET factor analysis to find the product opportunity gaps;using questionnaires and user interviews to research different high-speed railway travelers and derive various needs of users for high-speed railway seats;AHP was used to calculate and prioritize the target user requirements, and then QFD was used to determine the weights of each design requirement point. Conclusion: This paper aims to provide design ideas and future development trends for the design of high-speed railway seats in the post-pandemic era by using INPD, AHP and QFD methods. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Corona Virus or COVID-19 Disease is an infectious disease caused by newly discovered coronavirus. It caused a lot of damage to the Mankind around the world. It is also parallelly called as SARS-CoV-2 and was first reported in Wuhan City, China by the officials in December 2019. On 30 January 2020, the Director-General Tedros Adhanom of World Health Organization declared the outbreak of the coronavirus. Currently, many Pharma Companies aiming to develop vaccine to the COVID-19. To avoid being exposed to coronavirus, we must cover our nose and mouth with a mask, wash our hands frequently and avoid direct contact with the people who are already affected. This Paper aims to detect whether a person who is facing the camera is wearing a face mask or not in real time. Deep Learning is the best Technology present in the current Industry for its effectiveness in reorganization and classification using image processing. It proposes a retina face mask which a one stage detector and with further developments and modifications, this model can be used in Airports, Railway Stations and other highly crowed public areas.
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The relevance of the problem under study is stipulated by the need to stabilize the market for tourist services in existing restrictions caused by the SARS-CoV-2 pandemic. The purpose of the research: The purpose of the article is to develop integrated measures for the formation of transport and logistics clusters to increase the synergetic effect of the proposed activities aimed at raising the mobility level of potential consumers of tourist services. Methods of the research: The main research methods include predicting and simulating;they make it possible to consider the problem of forming the package of tourist and transport services as a process of targeted monitoring and optimization of tourist routes. Results of the research: The article presents the concept of the creation of the network of transport and tourist clusters in Poland and its functioning;large rail carriers are the core of the clusters. Practical significance: The proposed models for the formation of a package of tourist services are aimed at increasing the synergetic effect for all cluster participants, as well as at the development of tourist activities during the pandemic.
ABSTRACT
Crises have the potential to stimulate change processes in companies and tourism destinations alike. The aim of this paper is to investigate the COVID-19 crisis as a potential driver of innovations in tourism. As case study ski areas in Lower Austria are used, which in contrast to many other alpine regions were open in the winter season 2020/21. A document and internet analysis as well as interviews with decision makers were conducted to get insights into the preparation, implementation and evaluation of specific measures in the winter season 2020/21. The high demand pressure from the metropolitan area of Vienna posed a particular challenge to decision makers. With online tools and a supra-regional concept, new forms of digitization, visitor management, customer loyalty and pricing could be tested. The experiences made with these new measures during the 2020/21 season could help to make the tourism industry more resilient towards external stressors.