Clinical analysis of adenovirus pneumonia with pulmonary consolidation and atelectasis in children.

OBJECTIVE: To assess the clinical characteristics of 168 children with adenovirus pneumonia complicated by pulmonary consolidation and atelectasis. METHODS: We retrospectively studied patients with adenovirus pneumonia complicated by pulmonary consolidation and atelectasis admitted to Xiamen Children's Hospital from March 2019 to August 2019. In total, 168 patients were recruited and divided into a severe group and non-severe group according to disease severity. Clinical results were assessed. RESULTS: All children had fever and cough, 29 had wheezing, and 82 had dyspnea. Pleural effusion was found in 53 patients. Mixed infections were present in 95 patients. A total of 105 patients received hormone therapy, 72 received intravenous gamma globulin, and 103 underwent bronchoscopy, among whom 6 were found to have bronchial casts. Of the 168 children, 166 were cured and two died. The patients were divided by disease severity, with 82 in the severe group and 86 in the non-severe group. The two groups showed significant differences in the fever course, pleural effusion, mixed infections, hemoglobin concentration, procalcitonin concentration, and lactate dehydrogenase concentration. CONCLUSION: A long fever course, mixed infection, pleural effusion, decreased hemoglobin concentration, and increased procalcitonin and lactate dehydrogenase concentrations may be associated with more severe adenovirus pneumonia.

An Efficient Multiple Variants Coordination Framework for Differential Evolution.

Differential evolution (DE) is recognized as a simple but powerful algorithm in the family of evolutionary algorithms. Over the past two decades, many advanced DE variants with significantly improved performance have been proposed. However, the variants may only achieve the best performance on a certain type of functions. Moreover, a specific optimizer may not always be suitable for the whole optimization process. To overcome these weaknesses, this paper proposes a multiple variants coordination (MVC) framework with two mechanisms, namely, the multiple variants adaptive selecting mechanism and the multiple variants adaptive solutions preserving mechanisms (MV-APM). In MVC, the evolution process is divided into nonoverlap segments with equal numbers of generations. Each segment includes the learning generations (LGs) and executing generations (EGs). In LG, all the candidate DE optimizers are utilized independently. The best performing optimizer is determined and then utilized in EG in the same segment. Furthermore, MV-APM maintains the population by adaptively preserving promising solutions generated by multiple optimizers. Numerical experiments on the CEC2014 benchmark suit show that the proposed MVC framework can significantly improve the performance of the baseline algorithms and the resulted algorithm significantly outperform the start-of-the-art and up-to-date DEs. Moreover, as a general framework, MVC can also be applied to coordinate multiple improved DE variants to further enhance their performance.