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Regional Gray Matter Volume Related to High Occupational Stress in Firefighters
Lee Deokjong,Kim Woojin,Lee Jung Eun,Lee Junghan,Lee Seung-Koo,Chang Sei-Jin,Jeung Da Yee,Hyun Dae-Sung,Ryu Hye-Yoon,Kim Changsoo,Jung Young-Chul 대한의학회 2021 Journal of Korean medical science Vol.36 No.50
Background: Firefighters inevitably encounter emotionally and physically stressful situations at work. Even firefighters without diagnosed post-traumatic stress disorder receive clinical attention because the nature of the profession exposes them to repetitive trauma and high occupational stress. This study investigated gray matter abnormalities related to high occupational stress in firefighters using voxel-based morphometry (VBM) and surface-based morphometry (SBM). Methods: We assessed 115 subjects (112 males and 3 females) using magnetic resonance imaging and evaluated occupational stress by the Korean Occupational Stress Scale-26 (KOSS-26). Subjects were classified into highly or lowly stressed groups based on the median value of the KOSS-26. Results: In VBM analysis, we found that firefighters with high occupational stress had lower gray matter volume (GMV) in both sides of the insula, the left amygdala, the right medial prefrontal cortex (mPFC), and the anterior cingulate cortex than firefighters with low occupational stress. In SBM analysis based on regions of interest, the GMV of the bilateral insula and right mPFC were also lower in the highly stressed group. Within the highly stressed group, low GMV of the insula was significantly correlated with the length of service (left: r = −0.347, P = 0.009; right: r = −0.333, P = 0.012). Conclusion: Our findings suggest that regional GMV abnormalities are related to occupational stress. Regional gray matter abnormalities and related emotional dysregulation may contribute to firefighter susceptibility to burnout.
Oxygen-Controlled Seed Layer in DC Sputter-Deposited ZnO:Al Substrate for Si Thin-Film Solar Cells
Seung-Yoon Lee,Taehyun Hwang,Woojin Lee,Sangheon Lee,Hongsik Choi,Seh-Won Ahn,Heon-Min Lee,Byungwoo Park IEEE 2015 IEEE journal of photovoltaics Vol.5 No.2
<P>Oxygen-controlled seed layer in Al-doped ZnO (ZnO:Al) thin films deposited by the industrially compatible dynamic dc magnetron sputter results in both enhanced electron mobilities and appropriate etched morphologies for the Si thin-film solar cells. At the relatively low deposition temperature of 300 °C, optimized ZnO:Al film grown on the seed layer has the carrier mobility of 45 cm<SUP>2</SUP>/V·s and proper postetching morphology with around 1-2-μm crater size. Reduced angular distribution of the (002) grains analyzed by the diffraction rocking curve is shown as the key structural feature for the improved carrier mobility. Finally, the performance of the microcrystalline Si solar cell on the developed ZnO:Al substrate shows high-efficiency potential of the tandem solar cell adapting this transparent conductive oxide substrate.</P>
Nanostructural analysis of ZnO:Al thin films for carrier-transport mechanisms
Seung-Yoon Lee,Woojin Lee,남창우,Jongmin Kim,Sujin Byun,Taehyun Hwang,Byung-Kee Lee,Young Il Jang,Sungeun Lee,Heon Min Lee,박병우 한국물리학회 2013 Current Applied Physics Vol.13 No.4
The carrier mobility of sputter-deposited Al-doped ZnO transparent-conducting (ZnO:Al) thin films was controlled between 22 and 48 cm2/Vs by varying the ZnO:Al seed layer. The statistical distribution of the [001] grain misorientation was characterized from the X-ray diffraction rocking curve in the range from 0.043 (2.5) to 0.179 rad (10.2). The grain-boundary energy barriers (Eb) from Seto’s model [1] clearly exhibit linear dependence on the grain-boundary misorientation angle (u) according to the equation Eb ¼ 78 4 þ 173 32 u meV.
Instance Weighting Domain Adaptation Using Distance Kernel
Woojin Lee,Jaewook Lee,Saerom Park 대한산업공학회 2018 Industrial Engineeering & Management Systems Vol.17 No.2
Domain adaptation methods aims to improve the accuracy of the target predictive classifier while using the patterns from a related source domain that has large number of labeled data. In this paper, we introduce new kernel weight domain adaptation method based on smoothness assumption of classifier. We propose new simple and intuitive method that can improve the learning of target data by adding distance kernel based cross entropy term in loss function. Distance kernel refers to a matrix which denotes distance of each instances in source and target domain. We efficiently reduced the computational cost by using the stochastic gradient descent method. We evaluated the proposed method by using synthetic data and cross domain sentiment analysis tasks of Amazon reviews in four domains. Our empirical results showed improvements in all 12 domain adaptation experiments.
Woojin Lee,Se-Ryong Kang,Soon-Chul Choi,Sam-Sun Lee,Min-Suk Heo,Kyung-Hoe Huh,Won Jin Yi 한국물리학회 2016 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.69 No.2
The objective of this study was to develop a spectral CT system using a photon counting detector and to decompose materials by applying a multiple discriminant analysis (MDA) to the energy-dependent attenuation coefficient ratios. We imaged cylindrical phantoms of Polymethyl methacrylate (PMMA) with four holes filled with calcium chloride, iodine, and gold nanoparticle contrast agents. The attenuation coefficients were measured via reconstructed multi-energy images, and the linear attenuation ratio was used for material identification. The MDA projection matrix, determined from training phantoms, was used to identify the four materials in the testing phantoms. For quantification purposes, the relationships between the attenuation coefficients at multiple energy bins and the concentrations were characterized by using the least-squares method for each material. The mean identification accuracy for each of the three materials were 0.94 ± 0.09 for iodine, 0.96 ± 0.07 for gold nanoparticles, and 0.92 ± 0.05 for calcium chloride. The mean quantification errors were 1.90 ± 1.58% for iodine, 3.85 ± 3.13% for gold nanoparticle, and 3.40 ± 2.62% for calcium chloride. The developed multi-energy CT system based on the photon-counting detector with MDA can precisely decompose the four materials.