Final Doctoral Recital

Piano, Alban Berg, Alexander Scriabin, Charles Ives, Robert Schumann, Please see Additional Documents for Recital Program

Measuring Willingness to Accept for GM Food by Characteristics

Korean consumers' willingness to accept (WTA) for GM food are studied in this paper. This study compares hypothetical and nonhypothetical responses to choice experiment questions. We test for hypothetical bias in a choice experiment involving GM rice with differing characteristic attributes and multinomial logit model is applied to predict the estimated results. In general, hypothetical responses predicted higher probabilities of purchasing GM rice than nonhypothetical responses. Thus, hypothetical choices overestimate willingness to accept for GM rice. The results of this paper could contributes to government's GM food policies and subsequent studies, also improving economic welfare of farmers and consumers.GM Food, Willingness to Accept, Choice experiment, Hypothetical bias, Food Consumption/Nutrition/Food Safety,

Electron Parallel Closures for Various Ion Charge Numbers

Electron parallel closures for the ion charge number Z = 1 [J.-Y. Ji and E. D. Held, Phys. Plasmas 21, 122116 (2014)] are extended for 1 ≤ Z ≤ 10. Parameters are computed for various Z with the same form of the Z = 1 kernels adopted. The parameters are smoothly varying in Z and hence can be used to interpolate parameters and closures for noninteger, effective ion charge numbers

A Fomitopsis pinicola Jeseng Formulation Has an Antiobesity Effect and Protects against Hepatic Steatosis in Mice with High-Fat Diet-Induced Obesity

This study investigated the antiobesity effect of an extract of the Fomitopsis pinicola Jeseng-containing formulation (FAVA), which is a combination of four natural components: Fomitopsis pinicola Jeseng; Acanthopanax senticosus; Viscum album coloratum; and Allium tuberosum. High-fat diet-(HFD-) fedmale C57BL/6J mice were treated with FAVA (200 mg/kg/day) for 12 weeks to monitor the antiobesity effect and amelioration of nonalcoholic fatty liver diseases (NAFLD). Body and white adipose tissue (WAT) weights were reduced in FAVA-treated mice, and a histological examination showed an amelioration of fatty liver in FAVA-treated mice without decreasing food consumption. Additionally, FAVA reduced serumlipid profiles, leptin, and insulin levels compared with the HFD control group. The FAVA extract suppressed lipogenic mRNA expression levels from WAT concomitantly with the cholesterol biosynthesis level in the liver. These results demonstrate the inhibitory effects of FAVA on obesity and NAFLD in the diet-induced obese (DIO) mouse model. Therefore, FAVA may be an effective therapeutic candidate for treating obesity and fatty liver caused by a high-fat diet.110Nsciescopu

Benefits of personal music listening for family caregivers of critically ill patients during the post-COVID era

ObjectiveThis descriptive study surveyed family caregivers of patients in intensive care units (ICUs) during the COVID-19 pandemic to examine the impact of musical listening on their psychological well-being.MethodThe data collected in this study compared with collected from similar research conducted before the COVID-19 pandemic in 2017. The previous study had 195 participants, and the current study had 92. To measure the participants’ psychological well-being, the Korean version of the Center for Epidemiologic Studies Depression Scale and the World Health Organization Quality of Life Scale were administered. An investigator-constructed questionnaire was also used to collect information related to participants’ engagement in music activities including music listening in their everyday lives and their perceptions of music’s benefits.ResultsA two-way ANOVA showed significant effects for time (e.g., before vs. during COVID-19) and involvement in personal music listening (yes vs. no) on current emotional state, with family caregivers reporting significantly greater negative emotions during COVID-19 than before and personal music listening having a positive effect on perceived emotions. For quality of life there was no significant time effect, while the listening effect was statistically significant, indicating a significantly higher quality of life in the group who engaged in music listening in their everyday lives compared to the group who did not. There were no significant time or listening effects for perceived level of depression.ConclusionGiven the COVID-19 situation and the need to transition to a post-pandemic era, this study suggests that music listening can be an effective option for family caregivers to implement as a resource for attenuating emotional distress and enhancing self-care

Anti-Obesity Effects of Morus alba L. and Aronia melanocarpa in a High-Fat Diet-Induced Obese C57BL/6J Mouse Model

The present study investigated the synergic effect of extracts of Morus alba (MA) and Aronia melanocarpa (Michx.) (AR) against high-fat diet induced obesity. Four-week-old male C57BL/6J mice were randomly divided into five groups that were fed for 14 weeks with a normal diet (ND), high-fat diet (HD), HD with M. alba 400 mg/kg body weight (MA), HD with A. melanocarpa 400 mg/kg body weight (AR), or HD with a mixture (1:1, v/v) of M. alba and A. melanocarpa (400 mg/kg) (MA + AR). Treatment with MA, AR, and MA + AR for 14 weeks reduced high fat diet-induced weight gain and improved serum lipid levels, and histological analysis revealed that MA and AR treatment markedly decreased lipid accumulation in the liver and adipocyte size in epididymal fat. Furthermore, micro-CT images showed MA + AR significantly reduced abdominal fat volume. Expression levels of genes involved in lipid anabolism, such as SREBP-1c, PPAR-gamma, CEBP alpha, FAS, and CD36 were decreased by MA + AR treatment whereas PPAR-alpha, ACOX1, and CPT-1a levels were increased by MA + AR treatment. Protein expression of p-AMPK and p-ACC were increased in the MA + AR group, indicating that MA + AR ameliorated obesity by upregulating AMPK signaling. Together, our findings indicate that MA and AR exert a synergistic effect against diet-induced obesity and are promising agents for managing obesity

Effect of nickel on the microstructure and mechanical property of die-cast Al–Mg–Si–Mn alloy

The effect of nickel on the microstructure and mechanical properties of a die-cast Al–Mg–Si–Mn alloy has been investigated. The results show that the presence of Ni in the alloy promotes the formation of Ni-rich intermetallics. These occur consistently during solidification in the die-cast Al–Mg–Si–Mn alloy across different levels of Ni content. The Ni-rich intermetallics exhibit dendritic morphology during the primary solidification and lamellar morphology during the eutectic solidification stage. Ni was found to be always associated with iron forming AlFeMnSiNi intermetallics, and no Al3Ni intermetallic was observed when Ni concentrations were up to 2.06 wt% in the alloy. Although with different morphologies, the Ni-rich intermetallics were identified as the same AlFeMnSiNi phase bearing a typical composition of Al[100–140](Fe,Mn)[2–7]SiNi[4–9]. With increasing Ni content, the spacing of the α-Al–Mg2Si eutectic phase was enlarged in the Al–Mg–Si–Mn alloy. The addition of Ni to the alloy resulted in a slight increase in the yield strength, but a significant decrease in the elongation. The ultimate tensile strength (UTS) increased slightly from 300 to 320 MPa when a small amount (e.g. 0.16 wt%) of Ni was added to the alloy, but further increase of the Ni content resulted in a decrease of the UTS.The Engineering and Physical Sciences Research Council (EPSRC), Technology Strategy Board (TSB) and Jaguar Land Rover (JLR) in the United Kingdom

Improved Correction of Atmospheric Pressure Data Obtained by Smartphones through Machine Learning

A correction method using machine learning aims to improve the conventional linear regression (LR) based method for correction of atmospheric pressure data obtained by smartphones. The method proposed in this study conducts clustering and regression analysis with time domain classification. Data obtained in Gyeonggi-do, one of the most populous provinces in South Korea surrounding Seoul with the size of 10,000 km2, from July 2014 through December 2014, using smartphones were classified with respect to time of day (daytime or nighttime) as well as day of the week (weekday or weekend) and the user’s mobility, prior to the expectation-maximization (EM) clustering. Subsequently, the results were analyzed for comparison by applying machine learning methods such as multilayer perceptron (MLP) and support vector regression (SVR). The results showed a mean absolute error (MAE) 26% lower on average when regression analysis was performed through EM clustering compared to that obtained without EM clustering. For machine learning methods, the MAE for SVR was around 31% lower for LR and about 19% lower for MLP. It is concluded that pressure data from smartphones are as good as the ones from national automatic weather station (AWS) network