Background: Knee osteoarthritis is a highly prevalent chronic condition that affects approximately 80% of individuals aged ≥ 65 years. Major problems include pain, dysfunction, reduced quality of life, balance ability, and muscle tone. Objects: This study examined the effects of multidirectional knee-strengthening exercises using elastic bands on knee pain, functional disability, quality of life, balance ability, and rectus femoris (RF) muscle tone in elderly patients aged ≥ 65 years with knee osteoarthritis. Methods: Forty-eight patients aged ≥ 65 years with knee osteoarthritis participated in the study. The participants were assigned randomly to either the experimental group (n = 24) or the control group (n = 24). Both groups performed knee-strengthening exercises, but the experimental group incorporated elastic bands into their exercises. All interventions were conducted 3 times a week for 30 minutes per session over 4 weeks. The effects were assessed before and after the intervention using the Numeric Rating Scale (NRS), Korean version of the Western Ontario and McMaster Universities Arthritis Index (K-WOMAC), Euro Quality of Life 5 Dimension (EQ-5D), Berg Balance Scale (BBS), and RF muscle tone. Between-group differences before and after the intervention were analyzed using the independent t-test, and withingroup differences were examined using the paired t-test for pre-post intervention comparisons of the dependent variables. Results: Both groups showed significant improvements in the NRS, K-WOMAC function, KWOMAC total score, EQ-5D, BBS, and RF muscle tone after the intervention (p < 0.05). In addition, the experimental group showed significant improvements in the NRS, K-WOMAC, BBS, and RF muscle tone compared with the control group (p < 0.05). Conclusion: Multidirectional knee-strengthening exercises using elastic bands can be an effective intervention to improve knee pain, functional disability, balance ability, and RF muscle tone in elderly patients aged ≥ 65 years with knee osteoarthritis.

Background: The progressive digitalization of contemporary life, coupled with prolonged sedentary behavior, has contributed to the widespread occurrence of forward head posture (FHP) in the general population. Among the various exercise interventions aimed at correcting FHP, stretching exercises and proprioceptive training have garnered significant attention. Objectives: To investigate the effects of stretching exercises and proprioceptive training on craniovertebral angle (CVA), an indicator of forward head posture (FHP), and on the muscle tone of the suboccipital muscles. Design: Randomized controlled trial. Methods: Thirty participants were randomly assigned to either the stretching exercise group (n=15) or the proprioceptive training group (n=15), and each group underwent intervention three times per week for six weeks. CVA and muscle tone of the suboccipital muscles were measured before and after the six-week intervention, and the results were statistically analyzed for comparison. Results: Both groups showed a significant increase in CVA after the intervention (P<.05), with no significant difference between the groups. The muscle tone of the suboccipital muscles did not show statistically significant changes either within or between the groups. Conclusion: Six weeks of stretching exercise and proprioceptive training both resulted in a significant increase in CVA, demonstrating that both interventions are effective in improving FHP. However, neither intervention produced significant changes in the muscle tone of the suboccipital muscles.

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.

Efficient yet realistic ship routing is critical for reducing fuel consumption and greenhouse-gas emissions. However, conventional weather-routing algorithms often produce mathematically optimal routes that conflict with the paths mariners use. This study presents a hybrid approach that constrains physics-based weather routing within an AISderived maritime traffic network (MTN) built from one year of global Automatic Identification System data. The MTN represents common sea lanes as a graph of approximately 10,956 waypoints (nodes) and 17,561 directed edges. Using this network, an optimal low-emission route is computed via graph search and then compared against both a traditional unconstrained route and an advanced weather-routing model (VISIR-2). In a May transitionseason case (Busan–Singapore voyage), the AIS-constrained route reduced fuel consumption and CO₂ emissions by about 1.9% relative to the fastest feasible route, while closely following real traffic corridors (over 90% overlap with actual 2024 AIS tracks). While this 1.9% saving does not reach the high-end potential of an unconstrained, state-of-the-art model like VISIR-2 (which can demonstrate double-digit savings in certain conditions), it is achieved with an increase in transit time of ~6.5 h (≈3.2%). This represents a crucial trade-off, prioritizing operational realism and adherence to real-world traffic corridors over maximum theoretical efficiency.

본 연구는 환경 요인을 바탕으로 절화용 국화 생장 예측을 위한 최적의 모델을 개발하는 것을 목표로 하였다. 이를 위해 13개의 모델(Linear Regression, Lasso Regression, Ridge Regression, ElasticNet Regression, K-Nearest Neighbors (KNN), Support Vector Regression (SVR), Neural Network, Decision Tree, Random Forest, XGBoost, AdaBoost, CatBoost, Stacking)의 성능을 R2, MAE, RMSE를 평가 지표 로 비교하였다. 단일 모델 중에서는 Decision Tree가 가장 우수한 성능을 보였으며, R2값은 0.90에서 0.91 사이였다. 앙 상블 모델 중에서는 CatBoost가 가장 높은 성능을 보였으며 (R2=0.90~0.92) Random Forest와 XGBoost 또한 유사한 성 능을 보였다. 전체적으로 트리 기반 앙상블 모델이 국화 생장 예측에 적합한 모델로 나타났다.