ABSTRACT
Creating a good local microclimate can alleviate urban heat islands and poor urban ventilation. During the COVID-19 epidemic, citizens' cross-city and cross-regional activities were restricted, and most activities were conducted in open/semi-open areas next to residential areas, and local pedestrians were also quantitatively explored. The new characteristics of the microclimate bring difficulties. The RNG k-ε model in the Reynolds time-average method is used to simulate and analyze the wind environment of a typical street valley with a pocket park in a hot summer and a cold winter, and explore whether there are plants in the pocket park. The results show that the results obtained by the used turbulence model, initial edge conditions and numerical method are in good agreement with the selected verification experimental results, which meet the needs of the wind environment simulation of the pocket park. Only under the action of the pocket park, the pedestrian area is dimensionless. The difference in wind speed can reach 0.5 compared to the time when there is no park. When the plants in the park are added, the average wind speed in the pedestrian area of the surrounding street valley is less affected by the plants, and the dimensionless wind speed is only reduced by 0.1 in the core area of the park. Pocket parks can significantly improve the low wind speed in pedestrian areas, and the research results can provide reference for the design of low-carbon livable blocks and microclimate simulation during the epidemic period.
ABSTRACT
Background: The chest computed tomography (CT) had been used to define the diagnostic and discharge criteria for COVID-19. However, it is difficult to determine the suitability for discharge of a patient with COVID-19 based on CT features in a clinical setting. Deep learning (DL) technology has demonstrated great success in the medical imaging.Purpose: This study applied the novel deep learning (DL) on chest computed tomography (CT) of COVID-19 patients with consecutive negative respiratory pathogen nucleic acid test results at a “square cabin” hospital in Wuhan, China, with the intent to standardize criteria for discharge.Methods: The study included 270 patients (102men, 168 women; mean age, 51.9 ± 15.6[18–65] years) who had two consecutive negative respiratory pathogen tests (sampling interval: ≥1 day) and underwent low-dose CT 1 day after the first negative test, with strict adherence to epidemic prevention standards. The chest CT of COVID-19 patients with negative nucleic acid tests were evalued by DL, and the standard for discharge was a total volume ratio of lesions to lung of less than 50% determined by DL.Results: The average intersection over union is 0.7894. Fifty-seven (21.1%) and 213 (78.9%) patients exhibited normal lung findings and pneumonia, respectively. 54.0% (115/213) involved mild interstitial fibrosis. 18.8% (40/213) had total volume ratio of lesions to lung of more than and equal to 50% according to our severity scale and were monitored continuously in hospital, and three cases of which had a positive follow-up nucleic acid test during hospital observation. None of the 230 discharged cases later tested positive or exhibited pneumonia progression. Conclusions: The novel DL enables the accurate management of COVID-19 patients and can help avoid cluster transmission or exacerbation due to patients with false negitive acid test.