Background: Lung cancer is very common in China. The low cure rate, limited overall survival, and continuous therapies lead the patients to experience considerable psychological distress. Traditional Chinese medicine therapy is one unique treatment method in China. Nevertheless, most patients in the existing studies on anxiety and depression were treated in western medical hospitals. Therefore, it is necessary to identify the prevalence and risk factors of these emotional disorders in lung cancer patients treated in traditional Chinese medical hospitals. These findings may assist in clinical intervention. Patients and methods: A total of 315 patients with lung cancer were enrolled. Individuals completed the Hospital Anxiety and Depression Scale to assess their levels of anxiety and depression. Demographic and clinical data were also collected. Binary logistic regression analysis was used to identify factors that significantly predicted anxiety and depression. Results: The anxiety and depression prevalence rates of lung cancer patients were 43.5% and 57.1%, respectively. In the univariate analysis, patients without surgery, who were young, or who received radiotherapy were more likely to experience anxiety. Patients without surgery, who were young, or who had late-stage cancer, were more likely to experience depression. Binary logistic regression analysis showed that the risk factors of both anxiety and depression were lack of surgery and young and middle age (＜65, especially 45–65 years). Conclusion: Anxiety and depression were very common in lung cancer patients. Lack of surgery, young, and middle age, were independent risk factors for anxiety and depression. Therefore, medical workers should pay close attention to the emotional changes of young or middle-aged patients, or patients without the chance to undergo surgery.

Introduction:The recurrence rate of common bile duct stones (CBDS) after removal has been reported to exceed 10% and no established pharmacologic treatment exists for the prevention of recurrent CBDS. Many studies indicated ursodeoxycholic acid (UDCA) has the potential to prevent the recurrence of CBDS. The aim of this systematic review is to evaluate the effects of UDCA for prevention of recurrence after common bile duct stones removal.Methods and analysis:We will systematically screen all randomized controlled trials (RCTs) published through electronically and hand searching. The following search engines including Ovid Medline, EMBASE, Cochrane CENTRAL, Proquest, Scopus, Web of Science, Pubmed, the Chinese Biomedical Literature Database, the China National Knowledge Infrastructure, VIP Information, Wanfang Data. Supplementary sources will be searched including gray literature, conference proceedings, and potential identified publications in OpenGrey.eu and Google Scholar databases. Two reviewers will independently conduct the trial inclusion, data extraction and assess the quality of studies. The recurrence rate of CBDS will be assessed as the primary outcomes. The adverse event that required discontinuation of UDCA intervention and the drop-outs (lost to follow-up) before the end of the study will be measured as secondary outcomes. Methodological quality will be evaluated according to the Cochrane risk of bias. All analyses will be applied by RevMan (version 5.3).Results:This systemic review and meta-analysis will evaluate the effects of UDCA for prevention of recurrence after CBDS removal in RCTs.Conclusion:Our study will provide evidence to judge whether UDCA is an effective intervention to prevent the recurrence after CBDS removal.

IntroductionPatients with lung cancer often experience heavy psychological distress, especially depression, which results in poorer quality of life, shorter survival time and greater mortality. Our aim is to summarise data on the prevalence and risk factors of depression in patients with lung cancer.Methods and analysisWe will search PubMed, EMBASE, MEDLINE, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang and Chinese Biomedicine Literature Database (SinoMed) for studies on the prevalence and risk factors of depression in patients with lung cancer, which should be published from 1 January 1975 to 25 November 2018 in English/Chinese. Two reviewers will independently screen studies, extract data and assess the risk of bias. We will use RevMan V.5.0 and STATA V.12.0 software for statistical analysis. The I² test will be used to identify the extent of heterogeneity. Publication bias will be assessed by generating a funnel plot and performing the Begg and Egger test. The quality of the systematic review will be evaluated using the AMSTAR (‘A Measurement Tool to Assess Systematic Reviews’) criteria and ‘The Grading of Recommendations Assessment, Development and Evaluation’.Ethics and disseminationSince this is a review involving analysis of publicly available data, ethical approval is not required. The final results of this study will be published in a peer-reviewed journal.PROSPERO registration numberCRD42018118167.

For coal slurry pipeline blockage prediction problem, through the analysis of actual scene, it is determined that the pressure prediction from each measuring point is the premise of pipeline blockage prediction. Kernel function of support vector machine is introduced into extreme learning machine, the parameters are optimized by particle swarm algorithm, and blockage prediction method based on particle swarm optimization kernel function extreme learning machine (PSOKELM) is put forward. The actual test data from HuangLing coal gangue power plant are used for simulation experiments and compared with support vector machine prediction model optimized by particle swarm algorithm (PSOSVM) and kernel function extreme learning machine prediction model (KELM). The results prove that mean square error (MSE) for the prediction model based on PSOKELM is 0.0038 and the correlation coefficient is 0.9955, which is superior to prediction model based on PSOSVM in speed and accuracy and superior to KELM prediction model in accuracy.

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