Stemflow (SF) is essential for water resources within forest ecosystems and can constitute up to half of the gross rainfall (GR), depending on the forest stand structures in coniferous plantations. Although numerous studies on SF yield have been reported globally for various forest types, very few studies on SF have been reported to examine the influence of forest stand structures on SF in Korea. This study aimed to quantify the relationship between SF and forest stand structures in unmanaged Japanese cypress plantations. Two study plots were established (10 m × 10 m each) in plantations with the same stem density (SD: 2500 stems ha-1) (hereafter P1 and P2). Almost all forest stand structures (canopy projection area, tree height, diameter at breast height (DBH), number of live and dead branches, and ratio of canopy length to canopy width), including canopy volume using mobile LiDAR devices, were investigated. To evaluate the efficiency of funneling rainwater for the effect of tree biomass on SF, a funneling ratio (FR) was used. The present SF ratios (20.7% in P1 and 22.3% in P2) were much higher than those reported in previous studies of various forest types in Korea (SF ratios: 0.2–5.8% with a mean of 2.0%). This is due to the interaction between the high SD and many under-canopy dead branches. Individual-scale FR was correlated with DBH (R2 = 0.43). The present stand-scale FRs (FRstand) (22.3 in P1 and 29.2 in P2) were much higher than those reported in the previous studies (FRstand: 1.0–33.3 with a mean of 7.8) because of the negative relationship between FRstand and mean DBH (R2 = 0.78, p = 0.02). Our results provide useful information for understanding changes in SF caused by forest stand structures.

Sprout products, such as broccoli, alfalfa, and cabbage, have positive health effects. Thus far, sprout foods have attracted attention owing to their good bioavailability. In particular, young broccoli sprouts exhibit anti-inflammatory, antioxidant, and anti-cancer effects. They contain 100 times more chemoprotective substances than adult broccoli. This study examined the anti-inflammatory effects of freeze-dried young sprout broccoli (FD-YB) in vitro using RAW264.7 macrophage cells. The FDYB powder antioxidant ability test showed that the radical-scavenging activity and superoxide dismutase enzyme activity increased in a dose-dependent manner. In addition, FD-YB was not cytotoxic to RAW264.7 cells, and nitric oxide production decreased after the FD-YB treatment of lipopolysaccharide-stimulated RAW264.7 cells in a dose-dependent manner. Furthermore, FD-YB significantly decreased the expression of inflammation-related proteins (Cyclooxygenase-2, Inducible nitric oxide synthase, and Prostaglandin E Synthase 2) and cytokines (Tumor necrosis factor- and Interleukin-6). In conclusion, FD-YB can be a potential nutraceutical for preventing and regulating excessive immune responses during inflammation.

Salinity stress is a major threat to plant growth and development, affecting crop yield and quality. This study investigated the effects of different salinity levels on photosynthetic responses and bulb growth of Lilium LA hybrid “‘Serrada’.” Plants were irrigated with 1 L of 0, 200, and 400 mM NaCl solutions every two weeks for 14 weeks in a greenhouse. At the end of the cultivation period, the substrate pH decreased, and electrical conductivity increased with increasing salinity. Regardless of salinity levels, the days to flowering and number of flowers were similar among treatments. In contrast, the flower width, plant height, number of leaves, and leaf area decreased with increasing NaCl concentrations. Although there were no differences in the photosystem II (PSII) operating efficiency and maximum quantum yield of PSII, net CO2 assimilation rates (An) and stomatal conductance (gs) were significantly reduced at 200 and 400 mM NaCl solutions compared to the control. At 400 mM NaCl solution, bulb diameter and weight significantly decreased at the end of the experiment. These results suggest that bulb growth inhibition could be attributed to limiting photosynthetic rate and stem growth. This finding suggests that salinity mitigation is necessary to maintain plant growth and photosynthetic capacity in lily cultivation on salt-affected soils.

Rehmannia glutinosa root and Saururus chinensis plant have been widely used in natural traditional medicines. This study was conducted to investigate the effect of the content of the main components of R. glutinosa root and S. chinensis plant by extraction method. The results of comparative analysis of extraction yield, total flavonoid, and polyphenol content by extraction method indicated that extraction yield had the best performance with hot water extraction for R. glutinosa and ultrasound-assisted extraction for S. chinensis. The total flavonoid and polyphenol content had the best performance with maceration extraction for R. glutinosa and ultrasound-assisted extraction for S. chinensis. ABTS and DPPH activity was excellent with maceration extraction for both R. glutinosa and S. chinensis. The analysis of the main components showed that maceration extraction was most effective for both S. chinensis and R. glutinosa. Specifically, maceration extraction of R. glutinosa yielded 1.5 times more than conventional ultrasound-assisted extraction.

Since rice is the main food in Korea, there are no regulations on corn milling yet. Corn is known as one of the world's top three food crops along with wheat and rice, and it is known that 3.5 billion people worldwide use corn for food. In addition, corn mills are not developed or sold in Korea, but the use of corn mills is increasing significantly in many countries in Southeast Asia. In the Philippines, as Korea's rice mill import increases, Korea's KAMICO (Korea Agricultural Machinery Industry Cooperative) and domestic company A agreed to develop a corn mill jointly with PHilMech, an organization affiliated with the Philippine Ministry of Agriculture. However, research on corn milling was very insignificant, so the development was carried out based on the technology of Korea's rice mill. Rice milling is performed by peeling off the skin of rice and producing brown or white rice, so it is carried out by removing the skin and cutting the skin. On the other hand, in the corn mill, the skin of the corn is peeled, pulverized and selected to produce main products suitable for edible use. Therefore, in order to develop a corn mill, processes such as peeling, transfer, grinding, sorting, and by-product separation are required, and suitable parts must be developed. In addition, the performance must be gradually improved through experiments in which corn is repeatedly milled. The Philippines produces 7.98 million tons/year of corn, which is about 100 times that of Korea, and is mostly consumed as a staple food. This is about 10% of the total crop production in the Philippines. In addition, the main cultivation complexes of corn are the mountainous regions of Tarlac or Pangasinan, and the produced corn is 72.4% of the so-called yellow corn called Arabel and Sarangani, and the remaining 27.6% are known as white corn. In this study, it was intended to produce grains of 2.5 mm or less suitable for food for yellow corn and to develop a corn mill for 200 kg per hour. Detailed conditions for development are stipulated as more than 55% of the main product recovery rate, more than 31% of the by-product recovery rate, less than 5% of the raw material loss rate, and more than 80% of the embryo dislocation rate. In this study, to achieve this, the overall process of the corn mill was developed, and the optimal conditions for the corn mill were obtained through the development of parts and empirical tests to improve performance. In addition, it was intended to achieve the development goal by evaluating and analyzing the performance of each part so that it did not conflict.

This research examines the impact of visualizing virtual luxury products in the metaverse on consumers' perceptions of luxury products in the real world. We explore the metaverse as a marketing platform and investigate the relationship between the quality of visualization of virtual luxury products and consumers’ evaluations of real luxury products. The study hypothesizes that poor visualization quality of virtual luxury products will decrease the evaluation of authentic luxury goods, and this effect will be mediated by decreased perceived authenticity. Additionally, we predict that the negative effect will be mitigated by high-quality visualization.

Blockchain is an immutable ledger that records transactions and tracks assets using a common communication protocol. It stores a copy of the blockchain and implements a consensus function to verify transactions. Blockchain is applied to industries beyond finance, such as retail, to maintain security and transparency. Consumers with knowledge of blockchain technology are likely to be affected when evaluating products with blockchain embedded, impacting their product evaluation. The study investigates the impact of blockchain technology on consumers' product evaluation and how knowledge of blockchain and product quality moderate its effects.

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.