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The present study aimed to determine the pollution levels derived from polycyclic aromatic hydrocarbons (PAHs) in air, plant and soil samples and to reveal the PAH exchange at the soil-air, soil-plant and plant-air interfaces. In this context, air and soil samples were collected in approximately 10-day periods between June 2021 and February 2022 from a semi-urban area in Bursa, an industrial city with a dense population. Also, plant branch samples were collected for the last three months. Total PAH concentrations in the atmosphere (∑ 16 PAH) and soil (∑ 14 PAH) ranged from 4.03 to 64.6 ng/m 3 and 13-189.4 ng/g DM, respectively. PAH levels in the tree branches varied between 256.6 and 419.75 ng/g DM. In all air and soil samples, PAH levels were low in the summer and reached higher values in the winter. 3-ring PAHs were the dominant compounds, and their distribution in air and soil samples varied between 28.9%-71.9% and 22.8%-57.7%, respectively. According to the results of diagnostic ratios (DRs) and principal component analysis (PCA), both pyrolytic and petrogenic sources were found to be effective in PAH pollution in the sampling region. The fugacity fraction (ff) ratio and net flux (F net ) values indicated that the direction of movement of PAHs was from soil to air. In order to better understand the PAH movement in the environment, soil-plant exchange calculations were also achieved. The ratio of ∑ 14 PAH values measured to modeled concentrations (1.19net levels showed that branches were saturated with PAHs and the direction of PAH movement was from plant to soil. The plant-air exchange results indicated that the direction of movement of PAHs was from plant to air for low molecular weight PAHs and the opposite was true for compounds with high molecular weight ones., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yucel Tasdemir reports a relationship with Scientific and Technological Research Council of Turkey that includes: funding grants., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objectives: The objective of this study is to compare the various nonlinear and time series models in describing the course of the coronavirus disease 2019 (COVID-19) outbreak in China. To this aim, we focus on 2 indicators: the number of total cases diagnosed with the disease, and the death toll., Methods: The data used for this study are based on the reports of China between January 22 and June 18, 2020. We used nonlinear growth curves and some time series models for prediction of the number of total cases and total deaths. The determination coefficient (R2), mean square error (MSE), and Bayesian Information Criterion (BIC) were used to select the best model., Results: Our results show that while the Sloboda and ARIMA (0,2,1) models are the most convenient models that elucidate the cumulative number of cases; the Lundqvist-Korf model and Holt linear trend exponential smoothing model are the most suitable models for analyzing the cumulative number of deaths. Our time series models forecast that on 19 July, the number of total cases and total deaths will be 85,589 and 4639, respectively., Conclusion: The results of this study will be of great importance when it comes to modeling outbreak indicators for other countries. This information will enable governments to implement suitable measures for subsequent similar situations.

Objectives/hypothesis: The emergence of a new coronavirus strain (SARS-CoV-2) in December 2019 from China led to a global pandemic. The lack of herd immunity against this virus and the possibility of viral spread from asymptomatic individuals is still a major challenge for the prevention of viral transmission. The aim of this study was to evaluate the presence of the virus in different bodily secretions as a potential source of viral spread among patients infected with SARS-CoV-2., Study Design: Cross Sectional Study., Methods: The study included 38 COVID-19 patients with a positive real-time polymerase chain reaction (RT-PCR) test result for SARS-CoV-2, obtained from the combined nasopharyngeal-oropharyngeal swab samples. Saliva, tear, and cerumen samples were taken from the patients within 72 hours of the first RT-PCR test. SARS-CoV-2 N1 and N2 gene regions were studied with single-step RT-PCR in all samples., Results: Among the studied samples, the highest positivity rate was in saliva (76.3%) followed by tears (55.3%) and cerumen (39.5%). Viral load in saliva was also significantly higher compared to tears and cerumen (P < .001), while there was no significant difference between tears and cerumen. Higher viral load in combined nasopharyngeal-oropharyngeal swab samples was associated with higher viral load in tears, but not in saliva or cerumen. Half of the saliva, tear, and cerumen samples obtained from asymptomatic patients contained SARS-CoV-2 genome., Conclusions: The virus was detected in the saliva, tears, and cerumen samples of both symptomatic and asymptomatic patients. The potential role of these bodily fluids on viral spread needs to be studied., Level of Evidence: 4 Laryngoscope, 131:E1677-E1682, 2021., (© 2020 American Laryngological, Rhinological and Otological Society Inc, "The Triological Society" and American Laryngological Association (ALA).)