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Atmospheric Environment ; : 119304, 2022.
Article in English | ScienceDirect | ID: covidwho-1977051

ABSTRACT

A scarce distribution of the PM2.5 chemical compositions monitors reduces the applicability of scientific information for policymakers to assess the effectiveness of air pollution control strategies. There is an urgent need for a spatial-temporal prediction model for characterizing PM2.5 chemical compositions to assess exposure risks and develop effective air pollutants reduction strategies. In this study, the spatial-temporal variations of NO3− and SO42− were characterized using a hybrid multi-step ahead neural network (MSA-NN)/Kriging model in the urban areas with limited PM2.5 constituents monitoring stations. A meteorological normalization technique was further applied to develop a de-weather model to investigate temporal variations of air pollutants during the level 3 COVID-19 alert in central Taiwan. The MSA-NN algorithm could predict 94% and 91% of NO3− and SO42−, respectively, at the t+1-time horizon predictions. Based on the predicted results using the present de-weather model, the reduction in primary emissions attributed to the impact of COVID-19 during the level 3 alert was found to dominate the temporal air pollutant concentrations in central Taiwan. The present model could provide applicable and accurate high resolution of spatial-temporal NO3− and SO42− datasets in an area with limited PM2.5 chemical composition measurement. The present model could also be potentially applied to facilitate hotspot identification and human exposure assessment. The present Artificial Neural Network-based de-weather model is applicable to predict meteorological normalized time series air pollutant concentrations, which could be used to verify the effects of the meteorological parameters and primary emissions on the variations in air quality during the implementation of a specific air quality control strategy or changes in anthropogenic activities.

2.
Transplant Proc ; 54(6): 1575-1578, 2022.
Article in English | MEDLINE | ID: covidwho-1487992

ABSTRACT

We report a case of a heart transplant recipient who presented with a rapidly growing Epstein-Barr virus (EBV)-positive, diffuse large B-cell lymphoma 7 days after receiving the first dose of the ChAdOx1 nCoV-19 vaccine. Because of the atypical radiologic presentation, the initial tentative diagnosis was a mediastinal abscess. This observation indicates a potential risk of EBV reactivation after coronavirus disease 2019 (COVID-19) vaccination, which might lead to or aggravate the presentation of posttransplant lymphoproliferative disorder in transplantation patients. Transplant surgeons should be aware of the potential immunomodulatory effects of the COVID-19 vaccination.


Subject(s)
COVID-19 , ChAdOx1 nCoV-19 , Epstein-Barr Virus Infections , Heart Transplantation , Lymphoproliferative Disorders , Humans , ChAdOx1 nCoV-19/adverse effects , COVID-19/prevention & control , Epstein-Barr Virus Infections/complications , Epstein-Barr Virus Infections/diagnosis , Herpesvirus 4, Human , Lymphoproliferative Disorders/chemically induced , Lymphoproliferative Disorders/diagnosis
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