The objective of this study was to assess the effects of gypsum application on dry matter yield (DMY), mineral content of alfalfa (Medicago sativa L.), and soil properties in reclaimed tidal land in South Korea. The experiment was conducted in Seokmun, located on the west coast of South Korea, which is reclaimed with approximately 70 cm depth of degraded island soil. Treatments consisted of a control with no gypsum application (G0), 2 ton ha-1 (G2), and 4 ton ha-1 (G4) of gypsum application. The first harvest was carried out when the alfalfa reached 10% flowering, and subsequent harvests were conducted at 35-day intervals. Over the three-year experimental periods (2019-2021), the total DMY of G2 treatment was significantly higher than those of G0 and G4 (p<0.05). Although both G2 and G4 gypsum application treatments lowered soil pH, the G4 treatment increased the electrical conductivity (EC) content of the soil. Additionally, gypsum application affected the mineral contents of alfalfa, resulting in reduced concentration of sodium (Na) and Magnesium (Mg). Therefore, this present study suggests that a gypsum application rate of 2 ton ha-1 is optimal for improving alfalfa dry matter yield and mineral balance, as well as enhancing soil chemical properties in reclaimed tidal land in South Korea.

Nitrogen fertilizers are generally known to be of great help in improving crop yields, but excessive nitrogen fertilizer usage can not only destroy the environment but also negatively affect crop growth. This study aims to develop a decision-making system for optimal nitrogen fertilizer use for efficient production of Chinese cabbage (Brassica rapa), one of the major vegetables. The proposed system has the functions of detecting farmland based on satellite images, predicting cabbage yields and greenhouse gas (e.g., nitrous oxide) emissions according to nitrogen fertilizer use, and making decisions using the prediction results. To develop the proposed system, a generalized prediction model is developed using experimental data collected from South Korea, Egypt, India, Canada, Lithuania, and China, and the effectiveness of the proposed system is validated through experiments. As a result, the proposed system will enable farmers to conduct eco-friendly agricultural activities through appropriate nitrogen fertilizer use while stably maximizing productivity of Chinese cabbages.

Background: During daily activities, stability is maintained to enhance the function of muscles surrounding the lumbopelvic and hip structures. The core muscles such as the rectus abdominis (RA), external oblique (EO), and internal oblique (IO) responsible for this stability. One effective static exercise for strengthening these muscles is the plank. Objects: This study aimed to compare abdominal electromyographic activation when an unstable support surface was applied to the upper and lower extremities during a standard and a knee plank. Methods: A total of 30 adults (15 males and 15 females) participated in this study. Surface electromyography electrodes were placed on the RA, EO, and IO muscles. Data were collected under six conditions for males, including two plank postures (standard and knee planks) and three unstable surface conditions (a dynamic balance cushion applied to the upper extremities, lower extremities, or no cushion). Female participants performed only the knee plank. A mixed-effects model with a random intercept was used to analyze muscle activation across plank posture and surface position, with statistical significance set at α = 0.05. Results: In males, the standard plank elicited greater muscle activation than the knee plank across all muscles (p < 0.0001). Additionally, applying an unstable support surface to the upper extremities significantly increased muscle activation in both plank postures in EO and IO (p < 0.001). Other muscle, RA, was only affected by the unstable support surface in the standard plank position only. In females, the knee plank with upper limb instability resulted in the highest muscle activation for all muscles. Conclusion: These findings highlight the importance of surface instability in core muscle engagement. However, future studies should further investigate abdominal muscle activation with a more detailed analysis and the inclusion of a control group to enhance comparative validity.

This study was conducted to investigate the effects of feeding DDGS and full-fat soybean in the finishing diet on the performance, carcass characteristics and unsaturated fatty acid composition of Hanwoo steers. Thirty Hanwoo steers (average age, 26.4 months; weight, 756.69 kg) were assigned into Control (no additive), DS (DDGS supplemented) and FS (full-fat soybean supplemented). The feeding rate of DDGS and full-fat soybean was set at 10% and 5% in the finishing diet, respectively, and the in vivo trial was conducted for 122 days. The final body weight was 779.81, 774.20 and 791.95 kg for Control, DS and FS, respectively, and the average daily gain was not different among treatments. The feed conversion ratio was lower in FS compared to Control. Carcass cold carcass weight, backfat thickness, M. longissimus dorsi area and marbling scores were not different among treatments, and moisture, crude protein, and crude fat content in carcass were not different. The melting point of sirloin ranged from 25 to 26℃ among treatments. The saturated fatty acid, C18:0, was lower in the FS than in Control. C18:1, the main unsaturated fatty acid (UFA) in carcasses, did not show any difference among treatments, but C18:2 was higher in DS than in Control. Total UFAs were higher in the FS than in Control. Based on the above results, DDGS feeding was effective in improving feed conversion ratio and C18:2 content, and full-fat soybean feeding was effective in improving feed conversion ratio and increasing UFA content.

Galaxy evolution studies require the measurement of the physical properties of galaxies at different redshifts. In this work, we build supervised machine learning models to predict the redshift and physical properties (gas-phase metallicity, stellar mass, and star formation rate) of star-forming galaxies from the broad-band and medium-band photometry covering optical to near-infrared wavelengths, and present an evaluation of the model performance. Using 55 magnitudes and colors as input features, the optimized model can predict the galaxy redshift with an accuracy of σ(Δz/1+z) = 0.008 for a redshift range of z < 0.4. The gas-phase metallicity [12 + log(O/H)], stellar mass [log(Mstar)], and star formation rate [log(SFR)] can be predicted with the accuracies of σNMAD = 0.081, 0.068, and 0.19 dex, respectively. When magnitude errors are included, the scatter in the predicted values increases, and the range of predicted values decreases, leading to biased predictions. Near-infrared magnitudes and colors (H, K, and H −K), along with optical colors in the blue wavelengths (m425–m450), are found to play important roles in the parameter prediction. Additionally, the number of input features is critical for ensuring good performance of the machine learning model. These results align with the underlying scaling relations between physical parameters for star-forming galaxies, demonstrating the potential of using medium-band surveys to study galaxy scaling relations with large sample of galaxies.

Background: When shorter muscles are restored to normal, non-specific low back pain, which is the mechanism that causes pain along with muscle relaxation, disappears. Among the stretching methods, self-stretching is a good exercise method not only for treatment but also for preventive purposes. Objectives: To find out what is the most effective method of self-stretching, which is often used in treatment and preventive arbitration, which can reduce muscle activity and increase spinal flexibility in patients with non-specific back pain. Design: Randomized controlled trials. Methods: Three self-stretching exercise methods for erector spinae are randomly assigned to 13 people each, and three self-stretching exercise methods are performed for each study subject. Surface electromyography using, was performed to measure the erector spinae muscle activity. flexibility was measured through Trunk flexion test in a standing position. Muscle activity and flexibility were measured before and after stretching. Results: The difference in muscle activity and flexibility in the three groups, including cat stretching, seated stretching, and Reclining stretching, all showed statistically significant differences. There was no statistically significant difference in comparison between the three groups of stretch muscle activity. However, a statistically significant difference was shown in the comparison of the variability between the three groups of flexibility. In a post-mortem analysis comparing the amount of change in flexibility, the flexibility of the seated stretching in the chair increased significantly compared to the cat stretching group. Conclusion: It can be confirmed that the stretching method of the erector spinae, cat stretching, seated stretching, and Reclining stretching, all have positive effects on muscle activity and flexibility.

Background: Stroke patients often exhibit excessive kyphosis of the spine and a forward head posture (FHP), which negatively impacts their daily activities. These postural abnormalities not only negatively affect functional movement but also exacerbate musculoskeletal problems. Objectives: This study was conducted to determine the effect of backward walking on FHP in stroke patients. Design: Single-case experimental design (A-B-A’ design). Methods: The study was conducted over a total of 8 weeks, comprising 24 sessions: 3 baseline sessions (A), 18 intervention sessions (B), and 3 regression baseline sessions (A'). No backward walking intervention was performed during baseline (A) and regression baseline (A’). To determine changes in FHP, the craniovertebral angle (CVA) was measured at all sessions. Results: The CVA increased in the intervention (B) and regression baseline (A’) compared to the baseline (A). Conclusion: Backward walking was effective in improving FHP, and the effect was maintained after intervention (B) in patients with stroke. Therefore, backward walking was effective in improving the postural alignment of stroke patients.

Rapidly changing environmental factors due to climate change are increasing the uncertainty of crop growth, and the importance of crop yield prediction for food security is becoming increasingly evident in Republic of Korea. Traditionally, crop yield prediction models have been developed by using statistical techniques such as regression models and correlation analysis. However, as machine learning technique develops, it is able to predict the crop yield more accurate than the statistical techniques. This study aims at proposing the onion yield prediction framework to accurately predict the onion yield by using various environmental factor data. Temperature, humidity, precipitation, solar radiation, and wind speed are considered as climate factors and irrigation water and nitrogen application rate are considered as soil factors. To improve the performance of the prediction model, ensemble learning technique is applied to the proposed framework. The coefficient of determination of the proposed stacked ensemble framework is 0.96, which is a 24.68% improvement over the coefficient of determination of 0.77 of the existing single machine learning model. This framework can be applied to the particular farmland so that each farm can get their customized prediction model, which is visualized by the web system.

Recently, with the development of industrial technology and the increase of young consumers, engine monitoring devices for small ships are rapidly changing from analog devices to LCD-based digital devices. In addition, consumers’ product selection criteria are gradually increasing in favor of luxurious and emotional products rather than price attractiveness. Therefore, in order to develop differentiated products in marketing, it is necessary to find and improve emotionally attractive quality elements. The purpose of this study is to collect 11 customer requirements related to the emotional quality of DGP (Digital Gauge Panel) for small ships through customer interviews and to find attractive quality elements among the emotional qualities of DGP for small ships. 17 design elements were derived by applying QFD to the collected customer requirements, and they were classified into one-dimensional quality, must be quality, and attractive quality through Kano model analysis, and 6 attractive quality elements were confirmed using Timko customer satisfaction index.