• 생명과학회지
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• 제23권11호
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• pp.1381-1387
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• 2013

국내에서 식품으로 사용되고 있는 국화과 식물인 곤달비(Ligularia stenocephala) 잎과 뿌리의 생물활성을 과학적으로 검증하기 위하여 각 추출물에 대하여 항산화 활성 및 세포독성을 in vitro에서, 간보호 효과, 알코올 해독작용 및 기억증진 효능 등을 in vivo에서 평가하였으며 잎의 독특한 향기성분을 GC-MS로 분석하였다. 지질과산화 억제효과는 잎(20.4% 억제율)이 뿌리 보다 좋았으며, 유해 라디칼의 일종인 superoxide anion은 뿌리에서 생성 억제효과가 더 좋았고, DPPH 소거활성은 잎과 뿌리 모두 77~79%로 매우 뛰어났다. 사염화탄소로 유발된 급성 간독성 개선효과를 AST와 ALT 효소활성도를 지표로 확인한 결과, 잎의 ALT 억제활성이 대조군에 비해 약 78% 정도 감소하였으며 알코올을 투여한 mouse의 혈중 알코올 농도는 잎추출물 투여시 약 60% 가량 유의성 있게 감소되어 효과를 인정할 수 있었다. 세포독성은 뿌리에서 비교적 강하게 나타났는데, 흑색종의 경우, $IC_{50}=40.14mg/ml$이었으며, 잎의 세포독성은 비교적 약하였다. 기억증진 효과를 동물모델을 이용한 수동회피시험법으로 평가한 결과, 잎과 뿌리 모두 scopolamine에 의해 유도된 기억력 감소를 80% 이상 향상시킨 것으로 조사되었다. 곤달비 잎의 n-헥산 추출물을 GC-MS로 분석한 결과, 독특한 향기는 주로 terpene 화합물에서 유래되는 것으로 추정되었다.

• The Korean Journal of Physiology and Pharmacology
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• 제24권1호
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• pp.39-46
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• 2020

Alzheimer's disease (AD) is the most common neurodegenerative disorder causing dementia worldwide, and is mainly characterized by aggregated β-amyloid (Aβ). Increasing evidence has shown that plant extracts have the potential to delay AD development. The plant sterol β-Sitosterol has a potential role in inhibiting the production of platelet Aβ, suggesting that it may be useful for AD prevention. In the present study, we aimed to investigate the effect and mechanism of β-Sitosterol on deficits in learning and memory in amyloid protein precursor/presenilin 1 (APP/PS1) double transgenic mice. APP/PS1 mice were treated with β-Sitosterol for four weeks, from the age of seven months. Brain Aβ metabolism was evaluated using ELISA and Western blotting. We found that β-Sitosterol treatment can improve spatial learning and recognition memory ability, and reduce plaque load in APP/PS1 mice. β-Sitosterol treatment helped reverse dendritic spine loss in APP/PS1 mice and reversed the decreased hippocampal neuron miniature excitatory postsynaptic current frequency. Our research helps to explain and support the neuroprotective effect of β-Sitosterol, which may offer a novel pharmaceutical agent for the treatment of AD. Taken together, these findings suggest that β-Sitosterol ameliorates memory and learning impairment in APP/PS1 mice and possibly decreases Aβ deposition.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.582-588
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• 2018

Accident diagnosis is one of the complex tasks for nuclear power plant (NPP) operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN) has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM), which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents.

• KEPCO Journal on Electric Power and Energy
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• 제8권2호
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• pp.93-96
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• 2022

The boiler tubes of thermal power plants are exposed to harsh environment of high temperature and high pressure, and the deterioration state of materials rapidly increases. In particular, parent material and welds of the materials used are subjected to a temperature change and various constraints, resulting in deformation and its growth, resulting in frequent leakage accidents caused by tube failure. The power plant checks the integrity of boiler tubes through non-destructive testing as it may act as huge costs loss and limitation of power supply during power station shutdown period due to boiler tube leakage. However, the current non-destructive testing is extremely limited in the field to detect micro cracks. In this study, the ability of metal magnetic memory technique to detect flaws of size that are difficult to inspect by the visual or general non-destructive methods was verified in the early stage of their occurrence.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2000년도 제7차 국제 심포지움(생약자원개발에 관한연구) 및 추계정기 학술발표회 초록집
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• pp.14-14
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• 2000

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1998년도 The Korea Society for Simulation 98 춘계학술대회 논문집
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• pp.86-90
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• 1998

The safety and reliability of nuclear power plant operations relies heavily on the plant operators ability to respond to various emergency situations. It has become standard industry practice to utilize simulators to improve the safety and reliability of nuclear power plants operations. The simulators built for Younggwang#3,4, which is the basic model of the Korean Nuclear Power Plant design, has been developed precisely for this purpose. Dynamic Model and Display Model are developed under US3(UNIX Simulation Software Support System) environment in simulator for Younggwang#3,4. Since these two models are developed under each own operating system, it is necessary to develop a method for transporting data between these two systems. This paper descirves communication environment between Dynamic Model and Display Model, and addresses a file generation method for the Display Model, which will be necessary for designing MMI of MCR(Main Control Room) in the furture.

• Journal of Applied Biological Chemistry
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• 제49권3호
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• pp.110-113
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• 2006

Prolyl endopeptidase (PEP, EC 3.4.21.26, also referred to as prolyl oligopeptidase) degrades proline containing, biologically active neuropeptides such as vasopressin, substance P and thyrotropin-releasing hormone by cleaving peptide bonds on carboxyl side of prolyl residue within neuropeptides of less than 30 amino acids. Evaluation of PEP levels in postmortem brains of Alzheimer's disease patients revealed significant increases in PEP activity. Therefore, a specific PEP inhibitor can be a good candidate of drug against memory loss. Upon our examination for PEP inhibitory activity from micronutrients, ascorbic acid (vitamin C) showed small but significant PEP inhibition (13% PEP inhibition at $8{\mu}g{\cdot}ml^{-1}$). Palmitic acid showed almost no PEP inhibition. However, 6-O-palmitoyl ascorbic acid ($\underline{1}$) showed 70% PEP inhibition at $8{\mu}g{\cdot}ml^{-1}$ indicating that hydrophobic portion of the compound $\underline{1}$ may facilitate the inhibitory effect. $IC_{50}$ value of compound $\underline{1}$ was $12.6{\pm}0.2{\mu}M$. The primary and secondary Lineweaver Burk and Dixon plots for compound $\underline{1}$ indicated that it is a non-competitive inhibitor with inhibition constant (Ki) value of $23.7{\mu}M$.

• 식품보건융합연구
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• 제9권1호
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• pp.1-9
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• 2023

Polygala Tenuifolia, also described as Yuan Zhi, is a conventional botanic plant found in Korea and China. It's most well- known promise is to improve cognition and guard against mental disorders, cure sputum, anxiety, and sleeplessness, and keep the central nervous system health. The pharmacological aspects of Polygala Tenuifolia's genesis and component compounds reveal the neuroprotective potential in connection to Alzheimer's disease. It contains three herbs: Bokshin, Sukchangpo, and Wongi. P. Tenuifolia's primary ingredients are Xanthone glycosides, Triterpenoid saponins, and Oligosaccharides. Polygalasaponins and Etrahydrocolumbamine are the major components, and they've been widely used for more than a century to relieve mood and psychological illnesses, particularly in North Asian countries such as Korea, China, Japan, and Taiwan. P. Tenuifolia extract eliminates allergic illnesses such as eczema and contact dermatitis by modulating Protein kinase-A and Mitogen-protein kinase-38. In vitro and in vivo studies linking P. tenuifolia root ingredients to a variety of pharmacological effects pertinent to AD show that this species' isolates may function through polyvalency. In great health, people can take up to 250-300 mg per day. It was given in peer-reviewed studies at dosages of 100-150 mg many times each day. There is minimal evidence that it improves verbal memory in experimental animals.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1630-1643
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• 2023

The correct situation awareness (SA) of operators is important for managing nuclear power plants (NPPs), particularly in accident-related situations. Among the three levels of SA suggested by Ensley, Level 3 SA (i.e., projection of the future status of the situation) is challenging because of the complexity of NPPs as well as the uncertainty of accidents. Hence, several prediction methods using artificial intelligence techniques have been proposed to assist operators in accident prediction. However, these methods only predict short-term plant status (e.g., the status after a few minutes) and do not provide information regarding the uncertainty associated with the prediction. This paper proposes an algorithm that can predict the multivariate and long-term behavior of plant parameters for 2 h with 120 steps and provide the uncertainty of the prediction. The algorithm applies bidirectional long short-term memory and an attention mechanism, which enable the algorithm to predict the precise long-term trends of the parameters with high prediction accuracy. A conditional variational autoencoder was used to provide uncertainty information about the network prediction. The algorithm was trained, optimized, and validated using a compact nuclear simulator for a Westinghouse 900 MWe NPP.

• 제어로봇시스템학회논문지
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• 제13권4호
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• pp.279-285
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• 2007

The objective of the research is two fold. The first is to design and propose a stable and robust learning control algorithm. The controller is CMAC Learning Controller which consists of a model-based controller, such as LQR or PID, as a reference control and a CMAC. The second objective is to implement a reference control and CMAC at two different sampling rates. Generally, a conventional controller is designed based on a mathematical plant model. However, increasing complexity of the plant and accuracy requirement on mathematical models nearly prohibits the application of the conventional controller design approach. To avoid inherent complexity and unavoidable uncertainty in modeling, biology mimetic methods have been developed. One of such attempts is Cerebellar Model Articulation Computer(CMAC) developed by Albus. CMAC has two main disadvantages. The first disadvantage of CMAC is increasing memory requirement with increasing number of input variables and with increasing accuracy demand. The memory needs can be solved with cheap memories due to recent development of new memory technology. The second disadvantage is a demand for processing powers which could be an obstacle especially when CMAC should be implemented in real-time. To overcome the disadvantages of CMAC, we propose CMAC learning controller with multiple sampling rates. With this approach a conventional controller which is a reference to CMAC at high enough sampling rate but CMAC runs at the processor's unoccupied time. To show efficiency of the proposed method, an inverted pendulum controller is designed and implemented. We also demonstrate it's possibility as an industrial control solution and robustness against a modeling uncertainty.