Purpose -Since South Korea has widened its market doors to global trade, demand has been continuously on the rise for foreign luxury brands, especially from young South Korean consumers. This study aims to identify the determinants of young South Korean consumers' purchasing intentions toward foreign luxury fashion brands and their relative importance. Design/methodology/approach -The data used in this study were gathered by surveying university students in Seoul, South Korea using convenience sampling, and 319 questionnaires were used in the statistical analysis. In analyzing data, factor analysis, correlation, and regression were conducted. Findings -The results showed that all determinants, except for vanity, were significantly related to the purchasing of foreign luxury fashion brands. Regarding their relative importance, purchasing frequency was the most influential factor followed by conformity, age, consumer ethnocentrism, social recognition, and pocket money, in that order. Originality/value -For the luxury brand marketers, practical implications of why young South Korean consumers have increasing demands for foreign luxury brands, the potential market growth, consumer profiles, and marketing strategies were discussed.

We report on the hydrogen gas (H2) sensing performance of lithographically patterned Pd nanowires as a function of the nanowire thickness and H2 concentration. A combination of electron-beam lithography and a lift-off process has been utilized to fabricate four-terminal devices based on individual Pd nanowires with width w = 300 nm, length l = 10 microm, and thickness t = 20-400 nm from continuous Pd films. The variation of the resistance and sensitivity at 20 000 ppm H2 of Pd nanowires was found to be much lager than at 10 000 ppm H2, which can be explained by an alpha-beta phase transition occurring at 20 000 ppm H2. This is confirmed by the observation of hysteresis behavior in the resistance versus H2 concentration for Pd thin films. The response time was found to decrease with decreasing thickness regardless of H2 concentration due to a higher surface-to-volume ratio and a higher clamping effect. A single Pd nanowire with t = 100 nm was found to successfully detect H2 at a detection limit of 20 ppm. Our results suggest that lithographically patterned Pd nanowires can be used as hydrogen gas sensors to quantitatively detect H2 over a wide range of concentrations.

We present the hydrogen sensing performance of individual Pd nanowires grown by electrodeposition into nanochannels of anodized aluminum oxide (AAO) templates investigated as a function of the nanowire diameter. Four-terminal devices based on individual Pd nanowires were found to successfully detect hydrogen gas (H(2)). Our experimental results show that the H(2) sensing sensitivity increases and the response time decreases with decreasing diameter of Pd nanowires with d = 400, 200, 80 and 20 nm, due to the high surface-to-volume ratio and short diffusion paths, respectively. This is in qualitatively good agreement with simulated results obtained from a theoretical model based on a combination of the rate equation and diffusion equation.

Objective: This study was conducted to assess the clinical usability of the zero-echo time (ZTE) technique of MRI for evaluating bone changes of the temporomandibular joint (TMJ) in comparison with CBCT. Methods: Twenty patients with TMJ disorder who underwent both CBCT and MRI were randomly selected. CBCT images were obtained with an Alphard 3030 device (Asahi Roentgen Ind., Co. Ltd, Kyoto, Japan). MRIs were obtained using a 3.0 T scanner (Pioneer; GE Healthcare, Waukesha, WI, USA) and a 21-channel head coil. An isotropic three-dimensional proton-density-weighted ZTE sequence was acquired. Two radiologists evaluated 40 joints of 20 patients for the presence of the following osseous changes: flattening, erosion, osteophyte and sclerosis of the condyle; and flattening, erosion and sclerosis of the articular fossa. CBCT and ZTE-MRI assessments were performed at a 2-month interval. The prevalence-adjusted and bias-adjusted κ statistic was used to analyse interexaminer and intraexaminer agreement and the agreement between ZTE-MRI and CBCT. Results: Intraexaminer and interexaminer agreement analyses of ZTE-MRI showed high reproducibility (κ>0.80), which was comparable to that of CBCT. Flattening, osteophyte and sclerosis of the condyle and all types of bone changes in the mandibular fossa showed nearly perfect agreement between CBCT and ZTE-MRI (κ = 0.80–0.90). Erosion of the condyle showed substantial agreement between both sets of images (κ = 0.65–0.70). Conclusions: It is suggested that ZTE-MRI provides clinically reliable images for bone assessment in TMJ disorder. MRI may become a beneficial diagnostic tool for patients with both TMJ disc and bone pathology, with advantages involving medical costs and radiation dose.

Wavelength selection and prediction algorithm for determining total hemoglobin concentration are investigated. A model based on the difference in optical density induced by the pulsation of the heart beat is developed by taking an approximation of Twersky's theory on the assumption that the variation of blood vessel size is small during arterial pulsing. A device is constructed with a five-wavelength light emitting diode array as the light source. The selected wavelengths are two isobestic points and three in compensation for tissue scattering. Data are collected from 129 outpatients who are randomly grouped as calibration and prediction sets. The ratio of the variations of optical density between systole and diastole at two different wavelengths is used as a variable. We selected several such variables that show high reproducibility among all variables. Multiple linear regression analysis is made in order to predict total hemoglobin concentration. The correlation coefficient is 0.804 and the standard deviation is 0.864 g/dL for the calibration set. The relative percent error and standard deviation of the prediction set are 8.5% and 1.142 g/dL, respectively. We successfully demonstrate the possibility of noninvasive hemoglobin measurement, particularly, using the wavelengths below 1000 nm.

Glucose determination based on near-IR spectroscopy is investigated for reflectance and transmittance measurement. A wavelength range is 1100 to 2500 nm, which includes both the combination and overtone bands of glucose absorption. Intralipid solutions are used as samples, where glucose concentrations vary between 0 and 1000 mg/dl. Sample thickness for reflectance is 10 cm and 1- and 2-mm-thick samples are used for transmission. Partial least-squares regression (PLSR) analyses are performed to predict glucose concentrations. The standard errors of calibration are comparable between reflectance and 2-mm-thick transmittance. The reflectance method is inferior to the transmittance method in terms of the standard errors of prediction. Loading vector analysis for reflectance does not show glucose absorption features. Reflected light may not have enough information of glucose since a major portion of detected light has a short optical path length. In addition, prediction becomes more dependent on medium scattering rather than glucose, compared with transmission measurement. Loading vectors obtained from a PLSR transmittance analysis have glucose absorption profiles. The 1-mm-thick samples give better results than the 2-mm-thick samples for both calibration and prediction models. The transmittance setup is recommended for noninvasive glucose monitoring.

This study aimed to develop an artificial intelligence model that can detect mesiodens on panoramic radiographs of various dentition groups. Panoramic radiographs of 612 patients were used for training. A convolutional neural network (CNN) model based on YOLOv3 for detecting mesiodens was developed. The model performance according to three dentition groups (primary, mixed, and permanent dentition) was evaluated, both internally (130 images) and externally (118 images), using a multi-center dataset. To investigate the effect of image preprocessing, contrast-limited histogram equalization (CLAHE) was applied to the original images. The accuracy of the internal test dataset was 96.2% and that of the external test dataset was 89.8% in the original images. For the primary, mixed, and permanent dentition, the accuracy of the internal test dataset was 96.7%, 97.5%, and 93.3%, respectively, and the accuracy of the external test dataset was 86.7%, 95.3%, and 86.7%, respectively. The CLAHE images yielded less accurate results than the original images in both test datasets. The proposed model showed good performance in the internal and external test datasets and had the potential for clinical use to detect mesiodens on panoramic radiographs of all dentition types. The CLAHE preprocessing had a negligible effect on model performance.

The goal of this study was to develop a deep learning-based algorithm to predict temporomandibular joint (TMJ) disc perforation based on the findings of magnetic resonance imaging (MRI) and to validate its performance through comparison with previously reported results. The study objects were obtained by reviewing medical records from January 2005 to June 2018. 299 joints from 289 patients were divided into perforated and non-perforated groups based on the existence of disc perforation confirmed during surgery. Experienced observers interpreted the TMJ MRI images to extract features. Data containing those features were applied to build and validate prediction models using random forest and multilayer perceptron (MLP) techniques, the latter using the Keras framework, a recent deep learning architecture. The area under the receiver operating characteristic (ROC) curve (AUC) was used to compare the performances of the models. MLP produced the best performance (AUC 0.940), followed by random forest (AUC 0.918) and disc shape alone (AUC 0.791). The MLP and random forest were also superior to previously reported results using MRI (AUC 0.808) and MRI-based nomogram (AUC 0.889). Implementing deep learning showed superior performance in predicting disc perforation in TMJ compared to conventional methods and previous reports.