The trucking industry is the backbone of domestic supply chains. In the context of the COVID-19 pandemic, road transportation has been essential to guarantee the supply of basic goods to confined urban areas. However, the connectivity of the trucking network can also act as an efficient virus spreader. This paper applies network science to uncover the characteristics of the trucking network in one major Latin American country -Colombia- and provides evidence on freight networks' ability to spread contagious diseases spatially. Network metrics, official COVID-19 records at the municipality level, and a zero-inflated negative binomial model are used to test the association between network topology and confirmed COVID-19 cases. Results suggest that: (i) the number of COVID-19 cases in a municipality is linked to its level and type of network centrality; and (ii) being a port-city and a primary economic hub in the trucking network is associated with a higher probability of contracting earlier a pandemic. Based on these results, a risk-based approach is proposed to help policymakers implement containment measures.
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http://dx.doi.org/10.1016/j.tranpol.2021.10.022 | DOI Listing |
PLoS One
January 2025
Yunnan Tengjian Technology Co., Ltd, Kunming, China.
The rapid development of Internet of Things technology has promoted the popularization of Internet of Vehicles, and its safety and reliability have become the focus of intelligent transportation system research. Vehicle-road collaboration relies on the collaborative computing and storage resources of the vehicle on-board unit (OBU), which are usually limited. When the vehicle in the edge area needs to do computing tasks such as intelligent driving, but its own computing resources are insufficient.
View Article and Find Full Text PDFZhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi
December 2024
Laboratory of Occupational Protection and Ergonomics Research, National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
To investigate the changes of metabolites in urine of automobile manufacturing workers with muscle fatigue using metabolomics technology, and to explore potential biomarkers and disrupted metabolic pathways. In July 2022, urine samples were collected from 35 male workers in a certain automobile manufacturing industry before and after muscle fatigue, and metabolite analysis was conducted. Subsequently, multivariate statistical analysis was used for data processing to screen differential metabolites.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa, Saudi Arabia.
Accurate forecasting of claim frequency in automobile insurance is essential for insurers to assess risks effectively and establish appropriate pricing policies. Traditional methods typically rely on a Poisson distribution for modeling claim counts; however, this approach can be inadequate due to frequent zero-claim periods, leading to zero inflation in the data. Zero inflation occurs when more zeros are observed than expected under standard Poisson or negative binomial (NB) models.
View Article and Find Full Text PDFSci Rep
December 2024
Computer Science Department, Saarland University, Saarbrücken, Germany.
Estimating the numbers and whereabouts of internally displaced people (IDP) is paramount to providing targeted humanitarian assistance. In conflict settings like the ongoing Russia-Ukraine war, on-the-ground data collection is nevertheless often inadequate to provide accurate and timely information. Satellite imagery may sidestep some of these challenges and enhance our understanding of the IDP dynamics.
View Article and Find Full Text PDFJ Chromatogr A
December 2024
College of Environmental Science and Engineering, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China. Electronic address:
Here we covalently constructed abundant long-chain hydroxyl groups-functionalized magnetic microporous organic networks (MMON-2OH) for detection of eight Triazine herbicides (THs) in honey and water samples. MMON-2OH owned a high surface area (287.86 m²/g), enhanced water compatibility, and increased exposure of long-chain hydroxyl groups, which significantly improved enrichment capacity for THs.
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