An Explainable Prediction for Dietary-Related Diseases via Language Models.

Our study harnesses the power of natural language processing (NLP) to explore the relationship between dietary patterns and metabolic health outcomes among Korean adults using data from the Seventh Korea National Health and Nutrition Examination Survey (KNHANES VII). Using Latent Dirichlet Allocation (LDA) analysis, we identified three distinct dietary patterns: "Traditional and Staple", "Communal and Festive", and "Westernized and Convenience-Oriented". These patterns reflect the diversity of dietary preferences in Korea and reveal the cultural and social dimensions influencing eating habits and their potential implications for public health, particularly concerning obesity and metabolic disorders.

Enhancing Exchange-Traded Fund Price Predictions: Insights from Information-Theoretic Networks and Node Embeddings.

This study presents a novel approach to predicting price fluctuations for U.S. sector index ETFs.

Improving data efficiency for analyzing global exchange rate fluctuations based on nonlinear causal network-based clustering.

This study used information theory and network theory to predict the fluctuations of currency values of the machine learning model. For experiments, we calculate the causal relationships between currencies using loarithmic return (log-return) and entropic value-at-risk (EVaR) values of gold price per troy ounce in 48 currencies over 25 years. To quantify the causal relationships, we used the concept of transfer entropy.

Dietary Pattern Extraction Using Natural Language Processing Techniques.

In this study, we observed the changes in dietary patterns among Korean adults in the previous decade. We evaluated dietary intake using 24-h recall data from the fourth (2007-2009) and seventh (2016-2018) Korea National Health and Nutrition Examination Survey. Machine learning-based methodologies were used to extract these dietary patterns.

Detecting and Analyzing Politically-Themed Stocks Using Text Mining Techniques and Transfer Entropy-Focus on the Republic of Korea's Case.

Politically-themed stocks mainly refer to stocks that benefit from the policies of politicians. This study gave the empirical analysis of the politically-themed stocks in the Republic of Korea and constructed politically-themed stock networks based on the Republic of Korea's politically-themed stocks, derived mainly from politicians. To select politically-themed stocks, we calculated the daily politician sentiment index (PSI), which means politicians' daily reputation using politicians' search volume data and sentiment analysis results from politician-related text data.

Slurry Coating of Hydroxyapatite on Zirconia Substrate.

Zirconia dental implants require excellent biocompatibility and high bonding strength. In this study, we attempted to fabricate biocompatible zirconia ceramics through surface modification by hydroxyapatite (HA) slurry coating. A hydroxyapatite slurry for spin coating was prepared using two sizes of hydroxyapatite particles.

Effect of Powder Characteristics on Slip Casting Fabrication of Dental Zirconia Implants.

Dense zirconia compacts were fabricated by slip casting and sintering of nanoscale zirconia powders, and the effect of the powder characteristics (crystallite size, specific surface area, yttria content, and agglomeration) on the slurry and sintered properties was investigated. Three types of commercial 3 mol% yttria-stabilized tetragonal zirconia polycrystals powders were used as the starting powders after the powder characteristic analysis. A zirconia slurry for slip casting was prepared by mixing zirconia powder (solid loading of 60, 65, and 70 wt.

Effect of Solid Loading on the Sintered Properties of 3 mol% Yttria-Stabilized Tetragonal Zirconia Polycrystals (3Y-TZP) Ceramics via Slip Casting.

Dental zirconia implants fabricated by the mechanical machining and sintering of zirconia blocks have many surface cracks that lead to the deterioration of mechanical strength and the failure of the implant in the body. In this study, we attempted to manufacture an extremely dense and crack-free zirconia specimen by slip casting and pressureless sintering. After the preparation of zirconia slurry by control of its viscosity and by solid loading, highly dense zirconia specimens could be obtained by pressureless sintering at 1450 °C for 2 h.

A practical solution to improve the nutritional balance of Korean dine-out menus using linear programming.

Objective: We analysed optimal nutrient levels using linear programming (LP) to reveal nutritional shortcomings of Korean dine-out meals and to stress the importance of fruits and dairy products for maintaining a healthy diet.

Design: LP models that minimize deviation from recommended nutrient values were formulated to analyse deficiency or excess of nutrients under the best situation.

Setting: Korean dine-out menus and nutritional information were taken from the nutrient composition tables for dine-out menus developed by the Ministry of Food and Drug Safety and the nutrient database from Computerized Analysis Program.