• Korean Journal of Pharmacognosy
• /
• v.50 no.1
• /
• pp.59-64
• /
• 2019

Cudrania tricuspidata Bureau (Moraceae) has been used for physical weakness, impotence and insomnia in traditional Korean medicine. In this study, cudratricusxanthone A and cudraxanthone D were isolated from roots of C. tricuspidata and quantification were achieved by using high performance liquid chromatography (HPLC) method with diode array detector. The isolated compound was identified by NMR analysis and HPLC method was validated by linearity, precision and specificity test. The results showed that calibration curves of two compounds indicated great linearity with a correlation coefficient ($R^2$) of 0.9976 and 0.9995. The limits of detection (LOD) for cudratricusxanthone A and cudraxanthone D were 1.15, $0.11{\mu}g/ml$. Intra-day precision of cudratricusxanthone A and cudraxanthone D were 0.32~1.99%, 0.09~3.32% and inter-day precision were 0.59~2.40%, 0.28~1.55% RSD (%) values, respectively. The specificity was confirmed by chromatograph and quantitative contents of cudratricusxanthone A and cudraxanthone D were $0.46{\pm}0.02%$ and $1.53{\pm}0.06%$. Therefore, this study can be used as a basic research data for the quantitative analysis of derived compounds from roots of C. tricuspidata.

• Mass Spectrometry Letters
• /
• v.11 no.4
• /
• pp.82-89
• /
• 2020

A systematic isolation and characterization study for Cassia auriculata (CA) seeds resulted in identifying antidiabetic compounds 1,3,8-trihydroxyanthraquinone and quercetin, quercetin-3-O-rutinoside, gallic acid, caffeic acid, ferulic acid, and ellagic acid. The ultra-high-performance liquid chromatography based triple quadrupole mass spectrometry methodology was developed and validated for simultaneous identification and confirmation of these compounds from CA seeds. Multiple reaction monitoring (MRM) based quantification method was developed with MRM optimizer software for MS1 and MS2 mass analysis. The method was optimized on precursor ions and product ions with the ion ratio of each compound. The calibration curves of seven bioactive analytes showed excellent linearity (r2 ≥ 0.99). The quantitation results found precise (RSD, < 10 %) with good recoveries (84.58 to 101.42%). The matrix effect and extraction recoveries were found within the range (91.66 to 102.11%) for the CA seeds. This is the first MS/MS-based methodology applied to quantifying seven antidiabetic compounds in CA seeds and its extract for quality control purposes.

• Journal of Digital Convergence
• /
• v.19 no.2
• /
• pp.133-141
• /
• 2021

Recently, the number of seniors who engage in social and economic activities through digital platforms is increasing. Through this, they are building new social networks or creating profits. Therefore, this study aimed to conduct an in-depth interview with 17 seniors who are engaged in social and economic activities on a digital platform. This study examined their motivation and experience in detail through in-depth interviews. As a result of the study, three subjects (motivation for participation, evaluation and performance of activities, and requirements for stable activities) were derived. The results of this study are predicted to contribute to preventing social isolation of seniors by mediating digital platforms in the future and inducing them to become subjects of the digital economy.

• Korean Journal of Agricultural Science
• /
• v.48 no.2
• /
• pp.343-351
• /
• 2021

Screening was conducted using 200 kinds of plant extracts to explore herbicide-activated components of plant origin. We separated and purified active substances and elucidated chemical structures using Ligularia stenocephala M., which has strong activity and has not yet been studied. When the solvent fractions of the leaves of Ligularia stenocephala M. were tested for their herbicidal activity, ethyl acetate and chloroform layer showed an inhibition rate of 95.2% and 94.1%, respectively. In particular, the chloroform layer exerted more than 50% herbicidal activity at 10 ppm. From the chloroform layer with the highest herbicidal activity, we isolated three herbicidal active compounds using stepwise chromatography, specifically silica gel or octadecyl silica (ODS) column chromatography, Sep-pak cartridges, and high performance liquid chromatography (HPLC). Based on the analysis of the active compounds using electron ionization mass spectroscopy (EI-MS), ¹H-NMR, and ¹³C-NMR, we identified the active compounds as euparin, 5,6-dimethoxy-2-isopropenylbenzofuran, and liguhodgsonal. When the herbicidal activity of the identified compounds was tested, euparin showed selective herbicidal activity for lettuce at 10^-3 M, and both liguhogsonal and 5,6-dimethoxy-2-isoprophenylbenzofuran exerted selective activity for rice and Echinochloa crus-galli.

• Nuclear Engineering and Technology
• /
• v.55 no.2
• /
• pp.603-622
• /
• 2023

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.

• Structural Engineering and Mechanics
• /
• v.82 no.4
• /
• pp.417-434
• /
• 2022

In this work, a review of mechanical metamaterials and seismic protection systems that use them is carried out, focusing on passive protection systems. During the last years, a wide variety of classical systems of seismic protection have demonstrated to be an effective and practical way of reducing the seismic vulnerability of buildings, maintaining their health and structural integrity. However, with the emergence of metamaterials, which allow obtaining uncommon mechanical properties, new procedures and devices with high performance have been developed, reducing the seismic risk through novel approaches such as: seismic shields and the redirection of seismic waves; the use of stop band gaps and the construction of buried mass resonators; the design of pentamodal base isolators. These ideas are impacting traditional areas of structural engineering such as the design and building of highly efficient base isolation systems. In this work, recent advances in new seismic protection technologies and researches that integrate mechanical metamaterials are presented. A complete bibliometric analysis was carried out to identify and classify relevant authors and works related with passive seismic protection system based on mechanical metamaterial (pSPSmMMs). Finally, possible future scenarios for study and development of seismic isolators based on mechanical metamaterials are shown, identifying the relevant topics that have not yet been explored, as well as those with the greatest potential for future application.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.115-115
• /
• 2020

Water network partitioning (WNP) is an initiative technique to divide the original water distribution network (WDN) into several sub-networks with only sparse connections between them called, District Metered Areas (DMAs). Operating and managing (O&M) WDN through DMAs is bringing many advantages, such as quantification and detection of water leakage, uniform pressure management, isolation from chemical contamination. The research of WNP recently has been highlighted by applying different methods for dividing a network into a specified number of DMAs. However, it is an open question on how to determine the optimal number of DMAs for a given network. In this study, we present a method to divide an original WDN into DMAs (called Clustering) based on community structure algorithm for auto-creation of suitable DMAs. To that aim, many hydraulic properties are taken into consideration to form the appropriate DMAs, in which each DMA is controlled as uniform as possible in terms of pressure, elevation, and water demand. In a second phase, called Sectorization, the flow meters and control valves are optimally placed to divide the DMAs, while minimizing the pressure reduction. To comprehensively evaluate the WNP performance and determine optimal number of DMAs for given WDN, we apply the framework of multiple-criteria decision analysis. The proposed method is demonstrated using a real-life benchmark network and obtained permissible results. The approach is a decision-support scheme for water utilities to make optimal decisions when designing the DMAs of their WDNs.

• Biomedical Science Letters
• /
• v.29 no.4
• /
• pp.344-354
• /
• 2023

This study emphasizes the importance of early diagnosis and response to COVID-19, leading to the development of a rapid diagnostic kit using quantum dots. The research focuses on finely tuning bioconjugation with quantum dots to enhance the accuracy and sensitivity of COVID-19 diagnosis. We have developed a COVID-19 rapid diagnostic kit that exhibits a sensitivity more than 50 times higher than existing COVID-19 diagnostic kits. Quantum dots enable the accurate detection of COVID-19 viral antigens even at low concentrations, providing a rapid response in the early stages of infection. The COVID-19 quantum dot diagnostic kit offers quick analysis time, utilizing the quantum properties of particles to swiftly measure COVID-19 infection for immediate response and isolation measures. Additionally, this diagnostic kit allows for multiple analyses with ease, as multiple quantum dots can detect various antigens and antibodies simultaneously in a single experiment. This efficiency enhances testing, reduces sample requirements, and lowers experimental costs. The application of this diagnostic technology is anticipated in the future for early diagnosis and monitoring of other infectious diseases.

• Smart Structures and Systems
• /
• v.33 no.1
• /
• pp.27-39
• /
• 2024

The effectiveness of conventional tuned liquid dampers (TLDs) in controlling the wind-induced response of tall flexible structures has been indicated. However, the impaired control effect in the detuning condition or a considerably high mass cost of liquid may be incurred in ensuring the high-level serviceability. To provide an efficient TLD-based solution for wind-induced vibration control, this study proposes a serviceability-oriented optimal design method for isolated TLDs (ILDs) and derives analytical design formulae. The ILD is implemented by mounting the TLD on the linear isolators. Stochastic response analysis is performed for the ILD-equipped structure subjected to stochastic wind and white noise, and the results are considered to derive the closed-form responses. Correspondingly, an extensive parametric analysis is conducted to clarify a serviceability-oriented optimal design framework by incorporating the comfort demand. The obtained results show that the high-level serviceability demand can be satisfied by the ILD based on the proposed optimal design framework. Analytical design formulae can be preliminarily adopted to ensure the target serviceability demand while enhancing the structural displacement performance to increase the safety level. Compared with conventional TLD systems, the ILD exhibits higher effectiveness and a larger frequency bandwidth for wind-induced vibration control at a small mass ratio.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.11a
• /
• pp.227-228
• /
• 2023

A floating floor generally consists of mortar bed separated from the structural RC slab by a continuous resilient layer. It is known that the floating floors are a type of vibration-isolation system to improve the impact sound insulation performance. However, some researchers have demonstrated that the amplification of vibration response at a specific range of frequencies results in an increase in the impact sound level. This study carried out the forced vibration tests to obtain the frequency response function (FRF) of a floating floor compared with a bare RC slab. Test results shows that the additional peak occur in vibrational spectrum of the floating floor except natural vibration modes of the bare RC slab. This is because the relatively flexible resilient material and mass of the mortar bed offer an additional degree of freedom in the structural system. Therefore, it could be efficient for reduction of floor impact vibration and noise to control the additional mode frequency and response of floating floors.