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Anthropogenic nitrogen (N) inputs can have detrimental environmental effects, necessitating a comprehensive understanding of the nitrogen budget (NB) and its spatial correlation with the water quality. This study, utilizing a 2016 dataset, scrutinized 850 subwatersheds with diverse land covers across the Republic of Korea (ROK). Employing Geographically Weighted Regression (GWR), it examined the spatial correlations between the NBs and the quality of the groundwater and river water at the watershed scale. Robust correlations (R2 = 0.87) were observed between the groundwater quality and NBs, surpassing those of the surface water (R2 = 0.48). Sensitivity analyses highlighted the importance of high-resolution spatial data in capturing nuances within complex land covers. The integration of such data led to increases in the spatial correlations between the groundwater and river water quality of approximately 0.6–0.9 and 0.3–0.5, respectively. Notably, when the agricultural land cover exceeded 10%, significant enhancements in the spatial correlations were observed, emphasizing the pivotal role of agriculture in nutrient and water quality. At a 10% cropland ratio, the spatial correlations between the watershed-scale NBs and river/groundwater quality increased by approximately 76% and 501%, respectively. This study provides novel insights into the spatial relationships among NBs, water quality, and land use, highlighting the significance of high-resolution data and the impact of agricultural practices on watershed management. These findings contribute valuable information for developing strategies to mitigate nitrogen pollution.

Amid the ongoing global warming crisis, there has been growing interest in hydrogen energy as an environmentally friendly energy source to achieve carbon neutrality. A stable and large-scale hydrogen storage infrastructure is essential to satisfy the increasing demand for hydrogen energy. Particularly for hydrogen refueling stations located in urban areas, technological solutions are required to ensure the stability of adjacent civil structures in the event of hydrogen storage tank explosions. In this study, a numerical analysis using equivalent trinitrotoluene (TNT) and Concrete Damage Plasticity (CDP) models was employed to analyze the dynamic behavior of the ground in response to hydrogen gas explosions in shallow underground hydrogen storage facilities and to assess the stability of nearby structures against explosion effects. According to the simulation results, it was possible to ensure the structural stability of nearby buildings and tunnel structures by maintaining a minimum separation distance. In the case of nearby building structures, a distance of at least 6 to 7 m is needed to be maintained from the underground hydrogen storage facility to prevent explosion damage from a hydrogen gas explosion. For nearby tunnel structures, a distance of at least 10 m is required to ensure structural stability.

Ensuring the operational safety and reliability of rotary machinery systems, especially in oil plants, has become a focal point in both academic and industry arenas. Specifically, in terms of key rotary machinery components such as shafts, the diagnosis of these systems is paramount for achieving enhanced generalization capabilities in fault diagnosis, encompassing multiple sensor-derived variables with their respective fault patterns. This study introduces a multi-stage approach to generalize capabilities for fault diagnosis that considers multiple sensor-derived variables and their fault patterns. This method combines the Convolutional Triplet Network for feature extraction with an ensemble model for fault classification. Initially, vibration signals are processed to yield the most representative temporal and spatial features. Then, an ensemble approach is used to maximize both diversity and accuracy by balancing the contributions of the individual classifiers. The approach can detect three representative types of shaft faults more accurately than traditional single-stage machine learning models. Comprehensive experiments, detailed within, showcase the method’s efficacy in diagnosing rotary machine faults across diverse operational scenarios.

Plant-derived exosomes can exert therapeutic effects against various dermatological conditions. Several studies have demonstrated that plant-derived exosomes can have positive effects on the skin, preventing aging, hyperpigmentation, and hair loss. In this study, the protective effects of Iris germanica L. rhizome-derived exosomes (Iris-exosomes) on oxidative-stress-induced cellular dysfunction were investigated in human epidermal keratinocytes (nHEKs). Iris-exosomes with a diameter range of 100–300 nm were detected. In the cytotoxicity assay, Iris-exosomes with up to 107 particles per milliliter were found to possess no cytotoxicity, and we recovered H2O2-induced cell viability loss. In nHEKs, H2O2-induced ROS levels were significantly reduced using Iris-exosomes and additionally associated with increases in antioxidant enzyme transcription. The H2O2-induced SA-β-gal-positive nHEKs were decreased using Iris-exosomes; these effects correlate with the changed levels of cell cycle arrest marker p21. Furthermore, the H2O2-induced loss of in vitro wound-healing properties and early detection of keratin 1 and 10—keratinization markers—were restored to control levels using Iris-exosomes. Altogether, these results indicate the possibility that Iris-exosomes exert antioxidant and anti-senescence effects in order to protect against oxidative-stress-induced cellular dysfunction in nHEKs.

Water supply systems are essential elements for human life and industry, and water leaks and water supply cut-off may cause major problems. Local water leaks and pipe failures in the water supply system are inevitable problems due to the aging of pipes. Therefore, leakage detection and prevention are required to monitor the integrity of the water supply system. This paper is a fundamental study on the applicability of the smart bolt, which was developed as a monitoring system to detect water leakage in water supply monitoring. Detection experiments were conducted using a smart bolt with a built-in strain sensor and an accelerometer. Through finite element analysis using ANSYS 2019 R2 and tensile strength testing, the strength of the smart bolt was confirmed to have the acceptable tensile strength. The smart bolt used in this study was verified to meet the allowable criteria of torque and tensile stress for a municipal water supply system. The frequency responses of the simulated leakage pipe system, according to the leakage of the valve and the main pipe, were analyzed, and a leak signal at the valve leak point was detected in the 60-Hz band. The main pipe leaking point was observed to produce a leak signal with a much higher-order mode than that of the valve leak point. Therefore, the smart bolt can be applied to detect warning leak signs from water supply valves and to monitor for loosening of the bolts.

In order to detect damage to underwater infrastructure for inspection, an expensive survey by a diver is generally conducted, but it carries the risk of accidents. Accordingly, the development of an effective unmanned underwater survey system is an important priority. The unmanned underwater survey system used in this study is equipped with sonar towed by an- Unmanned Surface Vehicle (USV) to conduct the survey, but the USV is more affected by the waves and swells than a common boat. As a result, distorted sonar data causes errors in the information regarding the damage of underwater infrastructure. This study proposes the method of sonar image stabilization to minimize the errors of the distortion of sonar data by using a motion sensor. The change in the amount of the roll was calculated from the motion sensor, and the sonar data was corrected in the sonar ping unit. The sonar image stabilization algorithm was verified through field tests, and the error rate before and after correction was reduced by 15%. It is expected that, in the future, the proposed approach will be used as a standard data-gathering system for securing the reliability of sonar data when performing an unmanned underwater survey.

Insulin plays a key role in glucose homeostasis and is hence used to treat hyperglycemia, the main characteristic of diabetes mellitus. Annulohypoxylon annulatum is an inedible ball-shaped wood-rotting fungus, and hypoxylon F is one of the major compounds of A. annulatum. The aim of this study is to evaluate the effects of hypoxylonol F isolated from A. annulatum on insulin secretion in INS-1 pancreatic β-cells and demonstrate the molecular mechanisms involved. Glucose-stimulated insulin secretion (GSIS) values were evaluated using a rat insulin ELISA kit. Moreover, the expression of proteins related to pancreatic β-cell metabolism and insulin secretion was evaluated using Western blotting. Hypoxylonol F isolated from A. annulatum was found to significantly enhance glucose-stimulated insulin secretion without inducing cytotoxicity. Additionally, hypoxylonol F enhanced insulin receptor substrate-2 (IRS-2) levels and activated the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway. Interestingly, it also modulated the expression of peroxisome proliferator-activated receptor γ (PPARγ) and pancreatic and duodenal homeobox 1 (PDX-1). Our findings showed that A. annulatum and its bioactive compounds are capable of improving insulin secretion by pancreatic β-cells. This suggests that A. annulatum can be used as a therapeutic agent to treat diabetes.

Hydraulic factors account for a large part of the causes of bridge collapse. Due to the nature of the underwater environment, quick and accurate inspection is required when damage occurs. In this study, we developed a 2 MHz side scan sonar sensor module and effective operation technique by improving the limitations of existing sonar. Through field tests, we analyzed the correlation of factors affecting the resolution of the sonar data such as the angle of survey, the distance from the underwater structure and the water depth. The effect of the distance and the water depth and the structure on the survey angle was 66~82%. We also derived the relationship between these factors as a regression model for effective operating techniques. It is considered that application of the developed 2 MHz side scan sonar and its operation method could contribute to prevention of bridge collapses and disasters by quickly and accurately checking the damage of bridge substructures due to hydraulic factors.