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        Incipient fault diagnosis for centrifugal chillers using kernel entropy component analysis and voting based extreme learning machine

        Yudong Xia,Qiang Ding,Aipeng Jiang,Nijie Jing,Wenjie Zhou,Jian Wang 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.3

        Incipient fault detection and diagnosis for centrifugal chillers is significant for maintaining safe and effective system operation. Due to the advantages of simple learning algorithm and high generalization capability, the extreme learning machine (ELM) can identify faults quickly and precisely in comparison to conventional classification methods such as back propagation neural network (BPNN). This paper reports an effective diagnosis method for incipient chiller faults with the integration of kernel entropy component analysis (KECA) and voting based ELM (VELM). KECA was first performed to reduce the dimensionality of the original input data so as to minimize the model complexity and computational cost. Instead of using a single ELM, multiple independent ELMs were adopted in VELM, and then the class label could be predicted based on the majority voting method. Using the experimental data of seven typical faults together with a normal operation, the proposed KECA-VELM fault diagnostic model was trained and further validated. The results show that a better fault diagnosis performance can be achieved using the KECA-VELM classifier compared with the conventional BPNN, ELM and VELM based classifiers. The overall average fault diagnosis accuracy for the faults at the least severity level was reported over 95% based on the proposed method.

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        Excessive Daytime Sleepiness and Insomnia Symptoms in Adolescents With Major Depressive Disorder: Prevalence, Clinical Correlates, and the Relationship With Psychiatric Medications Use

        Yudong Shi,Wei Li,Changhao Chen,Xiaoping Yuan,Yingying Yang,Song Wang,Zhiwei Liu,Feng Geng,Jiawei Wang,Xiangfen Luo,Xiangwang Wen,Lei Xia,Huanzhong Liu 대한신경정신의학회 2023 PSYCHIATRY INVESTIGATION Vol.20 No.11

        Objective Excessive daytime sleepiness (EDS) and insomnia symptoms are common in patients with major depressive disorder (MDD), which might lead to a poor prognosis and an increased risk of depression relapse. The current study aimed to investigate the prevalence, and sociodemographic and clinical correlates of EDS and insomnia symptoms among adolescents with MDD.Methods The sample of this cross-sectional study included 297 adolescents (mean age=15.26 years; range=12–18 years; 218 females) with MDD recruited from three general and four psychiatric hospitals in five cities (Hefei, Bengbu, Fuyang, Suzhou, and Ma’anshan) in Anhui Province, China between January and August, 2021. EDS and insomnia symptoms, and clinical severity of depressive symptoms were assessed using Epworth sleepiness scale, Insomnia Severity Index, and Clinical Global Impression-Severity.Results The prevalence of EDS and insomnia symptoms in adolescents with MDD was 39.7% and 38.0%, respectively. Binary logistic regression analyses showed that EDS symptoms were significantly associated with higher body mass index (odds ratio [OR]=1.097, 95% confidence interval [CI]=1.027–1.172), more severe depressive symptoms (OR=1.313, 95% CI=1.028–1.679), and selective serotonin reuptake inhibitors use (OR=2.078, 95% CI=1.199–3.601). And insomnia symptoms were positively associated with female sex (OR=1.955, 95% CI=1.052–3.633), suicide attempts (OR=1.765, 95% CI=1.037–3.005), more severe depressive symptoms (OR=2.031, 95% CI=1.523–2.709), and negatively associated with antipsychotics use (OR=0.433, 95% CI=0.196–0.952).Conclusion EDS and insomnia symptoms are common among adolescents with MDD. Considering their negative effects on the clinical prognosis, regular screening and clinical managements should be developed for this patient population.

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        Piezo2: A Candidate Biomarker for Visceral Hypersensitivity in Irritable Bowel Syndrome?

        ( Tao Bai ),( Ying Li ),( Jing Xia ),( Yudong Jiang ),( Lei Zhang ),( Huan Wang ),( Wei Qian ),( Jun Song ),( Xiaohua Hou ) 대한소화기기능성질환·운동학회 2017 Journal of Neurogastroenterology and Motility (JNM Vol.23 No.3

        Background/Aims Currently, there exists no biomarker for visceral hypersensitivity in irritable bowel syndrome (IBS). Piezo proteins have been proven to play an important role in the mechanical stimulation to induce visceral pain in other tissues and may also be a biomarker candidate. The aim of this study was to test the expressions of Piezo1 and Piezo2 proteins in the intestinal epithelial cells from different intestinal segments and to explore the correlation between Piezo proteins expression and visceral pain threshold. Methods Post-infectious IBS was induced in mice via a Trichinella spiralis infection. Visceral sensitivity was measured with abdominal withdrawal reflex to colorectal distention. Inflammation in the small intestine and colon was scored with H&E staining. Expression location of Piezo proteins was confirmed by immunohistochemistry. Abundance of Piezo proteins were measured with real-time reverse transcriptase polymerase chain reaction. Results Piezo1 and Piezo2 proteins were expressed in the intestinal epithelial cells. The expression levels of Piezo1 and Piezo2 were abundant in the colon than the small intestine (P < 0.001 for Piezo1, P = 0.003 for Piezo2). Expression of Piezo2 in the colon significantly correlated to the visceral sensitivity (r = -0.718, P = 0.001) rather than the mucosal inflammation. Conclusion Piezo2 is a candidate biomarker for visceral hypersensitivity in IBS. (J Neurogastroenterol Motil 2017;23:453-463)

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