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Study on Springback Properties of Different Orthodontic Archwires in Archwire Bending Process
Jiang Jin-gang,Wang Zhao,Zhang Yong-de,Jiang Ji-xiong,Niu Suo-liang,Liu Yi 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.12
The archwire bending is one of processes the most frequently used in the orthodontic treatment. Furthermore, the springback of sheet metal, which is defined as elastic recovery of the part during unloading, should be taken into consideration so as to produce formed archwire within acceptable tolerance limits. In this paper, the springback angle of different alloy archwires (including NiTi alloy wire, Beta-Ti alloy wires, Chinese stainless steel wires, and Australian stainless steel wires) were performed by the theoretical calculation based on large deformation theory and the finite element analysis. A series of numerical simulations has been conducted for the bending test, which physically simulates the actual bending of alloy archwire with a robotic apparatus. The finite element analysis of springback is shown to be very consistent with the theoretical calculation results.
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Risk Factors for Anxiety in Major Depressive Disorder Patients
Li-Min Xin,Lin Chen,Zhen-Peng Ji,Suo-Yuan Zhang,Jun Wang,Yan-Hong Liu,Da-Fang Chen,Fu-De Yang,Gang Wang,Yi-Ru Fang,Zheng Lu,Hai-Chen Yang,Jian Hu,Zhi-Yu Chen,Yi Huang,Jing Sun,Xiao-Ping Wang,Hui-Chun 대한정신약물학회 2015 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.13 No.3
Objective: To analyze the sociodemographic and clinical factors related to anxiety in patients with major depressive disorder (MDD). Methods: This study involved a secondary analysis of data obtained from the Diagnostic Assessment Service for People with Bipolar Disorders in China (DASP), which was initiated by the Chinese Society of Psychiatry (CSP) and conducted from September 1, 2010 to February 28, 2011. Based on the presence or absence of anxiety-related characteristics, 1,178 MDD patients were classified as suffering from anxious depression (n=915) or non-anxious depression (n=263), respectively. Results: Compared with the non-anxious group, the anxious-depression group had an older age at onset (t=−4.39, p<0.001), were older (t=−4.69, p<0.001), reported more lifetime depressive episodes (z=−3.24, p=0.001), were more likely to experience seasonal depressive episodes (χ2=6.896, p=0.009) and depressive episodes following stressful life events (χ2=59.350, p <0.001), and were more likely to have a family history of psychiatric disorders (χ2=6.091, p=0.014). Their positive and total scores on the Mood Disorder Questionnaire (MDQ) and the 32-item Hypomania Checklist (HCL-32) (p<0.05) were also lower. The logistic regression analysis indicated that age (odds ratio [OR]=1.03, p<0.001), a lower total MDQ score (OR=0.94, p=0.011), depressive episodes following stressful life events (OR=3.04, p<0.001), and seasonal depressive episodes (OR=1.75, p=0.039) were significantly associated with anxious depression. Conclusion: These findings indicate that older age, fewer subclinical bipolar features, an increased number of depressive episodes following stressful life events, and seasonal depressive episodes may be risk factors for anxiety-related characteristics in patients with MDD.
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Xiao-Lin Luo,Ya-Shao Chen,Min-Juan Wang,De-Suo Yang,Jie Yang 한국공업화학회 2015 Journal of Industrial and Engineering Chemistry Vol.32 No.-
Cu2O micro-crystals with different morphologies (including three branching structures) weresynthesized through hydrothermal method by using sodium tartrate as chelating reagent. Branchinggrowth patterns of Cu2O microcrystals have a strong dependence on the amount of sodium tartrate. These different Cu2O microcrystals were used as catalysts to promote the thermal decomposition ofammonium perchlorate (AP). The thermal decomposition of AP in the presence or absence of Cu2Omicro-crystals was investigated non-isothermally through thermogravimetry and differential scanningcalorimetry (DSC). The data obtained from DSC were applied for the calculation and comparison of thekinetic parameters of AP decomposition process through a model-free approach.
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