Liu et al. Rapid advice guidelines for management of children with COVID-19
In view of the common and difficult to solve vehicle vibration problem, taking a large truck manufacturing enterprise in China as an example, an improved model for solving truck vibration problem is established by using the G8D method, and the unbalanced excitation force of the wheel system is analysed. The coupling of the excitation frequency and the natural frequency of the system leads to the resonance phenomenon, as well as the inadequate damping function of the system, is the fundamental cause of the vibration problem. After verifying and implementing permanent correction measures at the same time at the three levels of components, devices, and the entire vehicle, the acceleration of the seat guide rails for the vibration performance of the truck reduces from the original state 1.04 m/s2 to 0.6 m/s2, a decrease of 42.3%, which reaches the best level of mainstream cars in the country and is close to the optimal level of 0.5 m/s2 among the same kinds of cars in Germany. Therefore, the improved model can improve the sustainability of product manufacturing, provide industry guidance for solving the quality problem of truck vibration, and provide a sustainable guarantee for social public transport safety.
Children are the future of the world, but their health and future are facing great uncertainty because of the coronavirus disease 2019 (COVID-19) pandemic. In order to improve the management of children with COVID-19, an international, multidisciplinary panel of experts developed a rapid advice guideline at the beginning of the outbreak of COVID-19 in 2020. After publishing the first version of the rapid advice guideline, the panel has updated the guideline by including additional stakeholders in the panel and a comprehensive search of the latest evidence. All recommendations were supported by systematic reviews and graded using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Expert judgment was used to develop good practice statements supplementary to the graded evidence-based recommendations. The updated guideline comprises nine recommendations and one good practice statement. It focuses on the key recommendations pertinent to the following issues: identification of prognostic factors for death or pediatric intensive care unit admission; the use of remdesivir, systemic glucocorticoids and antipyretics, intravenous immunoglobulin (IVIG) for multisystem inflammatory syndrome in children, and high-flow oxygen by nasal cannula or non-invasive ventilation for acute hypoxemic respiratory failure; breastfeeding; vaccination; and the management of pediatric mental health. Conclusion : This updated evidence-based guideline intends to provide clinicians, pediatricians, patients and other stakeholders with evidence-based recommendations for the prevention and management of COVID-19 in children and adolescents. Larger studies with longer follow-up to determine the effectiveness and safety of systemic glucocorticoids, IVIG, noninvasive ventilation, and the vaccines for COVID-19 in children and adolescents are encouraged. What is Known: • Several clinical practice guidelines for children with COVID-19 have been developed, but only few of them have been recently updated. • We developed an evidence-based guideline at the beginning of the COVID-19 outbreak and have now updated it based on the results of a comprehensive search of the latest evidence. What is New: • The updated guideline provides key recommendations pertinent to the following issues: identification of prognostic factors for death or pediatric intensive care unit admission; the use of remdesivir, systemic glucocorticoids and antipyretics, intravenous immunoglobulin for multisystem inflammatory syndrome in children, and high-flow oxygen by nasal cannula or non-invasive ventilation for acute hypoxemic respiratory failure; breastfeeding; vaccination; and the management of pediatric mental health. Supplementary Information The online version contains supplementary material available at 10.1007/s00431-022-04615-4.
In order to improve the production capacity of traditional wood manufacturing industry, efficient wood quality and thickness detection is a challenging issue. This paper firstly carries out digital twin modeling for a drawer side panel processing line of a wood company and explores the efficiency problems existing in the links of quality inspection and thickness inspection of wood by means of value stream mapping. Therefore, we adopted a lightweight convolution neural network MobileNetV2 for wood quality detection, which realized efficient wood quality identification. In contrast, traditional convolution neural network has many weighting parameters and large scale of generating detection model, which makes it difficult to apply in situations with limited computing power and memory. Secondly, due to the stronger robustness and generalization ability of the residual network, we used ResNet to detect the wood thickness and obtain reliable performance. Finally, we reasonably embedded them in the whole wood production process and established the simulation model of production line before and after improvement in FlexSim simulation software. The experimental results show that the improved plan can simplify the workshop production process, increase the production balance rate by 29.07%, increase the product value-added rate from 0.08% to 0.11%, and shorten the production cycle by 2 hours. Performance indicators such as product inventory, number of people, and equipment utilization also improve significantly. Based on the above results, the validity of the production process improvement model proposed by US based on lightweight convolution and deep residual network is demonstrated.
As one of the core methods of the quality management system in the automotive industry, the process approach is an important tool for realizing the quality assurance of complex manufacturing systems with multi-sector, multi-process and multi-quality indicators. This paper first gives an overview of the quality management in the automotive industry, and then introduces the research status of the quality management system based on process approach in the industry, providing direction for the automotive industry in both research and practice of process-approach based quality management models.
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