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Supplemental material, sj-docx-3-his-10.1177_11786329221134352 for Gaps in the Utilization of Community Health Services for the Elderly Population in Rural Areas of Mainland China: A Systematic Review Based on Cross-Sectional Investigations by Shanshan Deng, Chenchen Zhang, Xing Guo, Hekai Lv, Yanyan Fan, Zhuoxin Wang, Dan Luo, Xiaoxia Duan, Xinying Sun and Fuzhi Wang in Health Services Insights

Supplemental material, sj-docx-1-his-10.1177_11786329221134352 for Gaps in the Utilization of Community Health Services for the Elderly Population in Rural Areas of Mainland China: A Systematic Review Based on Cross-Sectional Investigations by Shanshan Deng, Chenchen Zhang, Xing Guo, Hekai Lv, Yanyan Fan, Zhuoxin Wang, Dan Luo, Xiaoxia Duan, Xinying Sun and Fuzhi Wang in Health Services Insights

Supplemental material, sj-docx-2-his-10.1177_11786329221134352 for Gaps in the Utilization of Community Health Services for the Elderly Population in Rural Areas of Mainland China: A Systematic Review Based on Cross-Sectional Investigations by Shanshan Deng, Chenchen Zhang, Xing Guo, Hekai Lv, Yanyan Fan, Zhuoxin Wang, Dan Luo, Xiaoxia Duan, Xinying Sun and Fuzhi Wang in Health Services Insights

Supplemental material, sj-docx-7-his-10.1177_11786329221134352 for Gaps in the Utilization of Community Health Services for the Elderly Population in Rural Areas of Mainland China: A Systematic Review Based on Cross-Sectional Investigations by Shanshan Deng, Chenchen Zhang, Xing Guo, Hekai Lv, Yanyan Fan, Zhuoxin Wang, Dan Luo, Xiaoxia Duan, Xinying Sun and Fuzhi Wang in Health Services Insights

Supplemental material, sj-docx-6-his-10.1177_11786329221134352 for Gaps in the Utilization of Community Health Services for the Elderly Population in Rural Areas of Mainland China: A Systematic Review Based on Cross-Sectional Investigations by Shanshan Deng, Chenchen Zhang, Xing Guo, Hekai Lv, Yanyan Fan, Zhuoxin Wang, Dan Luo, Xiaoxia Duan, Xinying Sun and Fuzhi Wang in Health Services Insights

Supplemental material, sj-docx-5-his-10.1177_11786329221134352 for Gaps in the Utilization of Community Health Services for the Elderly Population in Rural Areas of Mainland China: A Systematic Review Based on Cross-Sectional Investigations by Shanshan Deng, Chenchen Zhang, Xing Guo, Hekai Lv, Yanyan Fan, Zhuoxin Wang, Dan Luo, Xiaoxia Duan, Xinying Sun and Fuzhi Wang in Health Services Insights

BACKGROUND Over the past two decades, the prevalence of autism spectrum disorder (ASD) among children worldwide has been rising rapidly. While Lab-based test were commonly used in the clinical diagnosis of autism, it is not feasible to test all new-borns for autism. OBJECTIVE This study focused on the risk factors of children with autism in the pre-pregnancy, early gestational (first month to six month) and perinatal stages as proposed by clinical epidemiological studies, and applied a deep learning artificial neural network to establish an early warning model of children with autism. METHODS A multivariate questionnaire on risk factors for autism in children was developed in this study. Parents of children with (n = 137) and without autism (n = 186) in five Chinese cities were investigated. The data were split into two completely independent datasets: training set (80%) and test set (20%). The sensitivity, specificity, and accuracy of four risk factor set (RFS) models were compared. The AUCs of four prediction models were also compared. RESULTS The sensitivity and accuracy values of the RFS-B model were superior to those of the other three models. The specificity of the RFS-C was superior to that of the other three models. The AUCs of the four RFS models were computed to be 0.876, 0.905, 0.850 and 0.870. CONCLUSIONS The results of the present study indicate that the deep learning artificial neural network has potential value in early risk prediction for children with autism.

There has been growing interest in using trenchless technology, especially centrifugal spraying techniques, to renovate the sewer pipe network in China. In this study, a damaged reinforced concrete pipe (RCP) (i.e., 14.7% vertical deformation) with one-meter diameter is rehabilitated by centrifugally spraying on a 50 mm thickness mortar lining. The ultimate (Du) D-load only increased by 2% compared to host pipe’s residual strength; however, other pipe properties exhibited improvement. Based on the behavior of two experimental results, finite element models were established, and an innovative pipeline damage quantization model was proposed. Through parameter sensitivity analysis, the effects of interface strength and fracture energy on pipe bearing capacity were studied. It was discovered that interface bonding performance affected the service load of the rehabilitated pipe. From the analysis of pipeline initial state deformation influence on the repaired structure bearing capacity, it was discovered that selecting a reasonable repair time point can effectively improve the functionality of the pipe network and reduce repair costs. An analysis of RCPs structural repair with a vertical deformation larger than 14% revealed that it is difficult to repair damaged pipes only employing mortar spraying. A structural design method based on the service load and ultimate load is presented in this paper.