he emergence and prevalence of drug-resistant bacteria caused by overuse of antibiotics pose new challenges to the treatment of bacterial infections. In this work, the hollow mesoporous CuO nanozymes (HM-CuO...

Climate change and urban heat island effects affect the energy consumption of buildings in urban heat islands. In order to meet the requirements of engineering applications for detailed daily design parameters for air conditioning, the 15-year summer meteorological data for Beijing and Shanghai and the corresponding average heat island intensity data were analyzed. Using the CRITIC objective weighting method and K-means clustering analysis, the hourly change coefficient, β, of dry bulb temperature was calculated, and the LSTM algorithm was used to predict the changing trends in β. Finally, the air conditioning load model for a hospital was established using DeST (version DeST3.0 1.0.2107.14 20220712) software, and the air conditioning cooling load in summer was calculated and predicted. The results show that, compared with the original design days, regional differences in the new design days are more obvious, the maximum temperature and time have changed, and the design days parameters are more consistent with the local meteorological conditions. Design day temperatures in Shanghai are expected to continue rising for some time to come, while those in Beijing are expected to gradually return to previous levels. Among hospital buildings, the cooling load of outpatient buildings in Beijing and Shanghai will decrease by 0.69% and increase by 12.61% and by 12.12% and 15.51%, respectively, under the influence of the heat island effect. It is predicted to decrease by 1.35% and increase by 29.75%, respectively, in future. The cooling load of inpatient buildings in Beijing and Shanghai increased by 0.27% and 6.71%, respectively, and increased by 7.13% and 8.09%, respectively, under the influence of the heat island effect, and is predicted to decrease by 0.93% and increase by 16.07%, respectively, in future.

The natatorium’s ventilation problem receives much concern because of its large wet load. The outdoor humidity ratio in transition season is the basic design parameter of the ventilation calculation, directly affecting the rationality of architectural design. At present, the ventilation-curve (V-C) method is the most widely used method to determine the outdoor humidity ratio in the transition season in China. However, due to failing to reflect non-guaranteed hours, the rationality of this value is difficult to assess by employing this approach. This paper presents a new method, the typical transition season method (TTS), for determining the outdoor humidity ratio in the transition season of a natatorium. The TTS method selects the transition season based on the typical meteorological year (TMY) data and calculates the outdoor humidity ratio with multiple non-guaranteed hours. This can well-represent the local perennial climate characteristics and clearly reflect the non-guaranteed hours. In this study, through selecting six typical representative cities in China, the evaluation of the outdoor humidity ratio is achieved through calculating ventilation volume and air change rate, verifying the rationality of this method. The results show that the humidity ratio obtained by the V-C method is lower than that obtained by the TTS method at about 2 g/kg without guarantee of 200 h humidity ratio, and even that the maximum difference is 6.64 g/kg. Meanwhile, the validation results of the ventilation calculation show that the humidity ratio determined by the V-C method cannot meet the minimum design requirements in five cities, while the humidity ratio obtained by the TTS method cannot meet the requirements in only one city.

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