• Toxicological Research
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• 제25권1호
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• pp.1-8
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• 2009

Validation specifies and coordinates all relevant activities to ensure compliance with good laboratory practices (GLP) according to suitable international standards. This includes validation activities of past, present and future for the best possible actions to ensure the integrity of non-clinical laboratory data. Recently, validation has become increasingly important, not only in good manufacturing practice (GMP) institutions but also in GLP facilities. In accordance with the guideline for GLP regulations, all equipments used to generate, measure, or assess data should undergo validation to ensure that this equipment is of appropriate design and capacity and that it will consistently function as intended. Therefore, the implantation of validation processes is considered to be an essential step in a global institution. This review describes the procedures and documentations required for validation of GLP. It introduces basic elements such as the validation master plan, risk assessment, gap analysis, design qualification, installation qualification, operational qualification, performance qualification, calibration, traceability, and revalidation.

• 비파괴검사학회지
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• 제24권4호
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• pp.396-409
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• 2004

음향방출기술(acoustic emission technology)은 종래의 기존 비파괴검사법과는 달리 가동중인 설비의 건전성을 평가할 수 있으며 실시간으로 설비 상태의 진단이 가능한 실시간 감시기법이다. 즉 기존 비파괴검사법과는 달리 가동중인 설비에 대해 원격으로 결함을 탐지하고 결함 위치를 판정할 수 있는 연속감시 기능을 가진 비파괴 신기술로 최근 연구개발이 활발히 진행되고 있는 방법이다. 이러한 장점 때문에 대형 산업설비의 각종 기기들에 대한 감시 및 진단에 활용하고 있으며, 그 활용도가 점점 확대되고 있는 추세에 있다. 특히 종합적인 산업설비로 구성되어 있는 발전설비의 진단과 감시에 가장 효과적인 방법이라 할 수 있겠다. 본 논문에서는 원자력 화력 수력발전소 등의 발전설비에 대해 현재 적용중인 음향방출기술과 새로운 적용기술에 대해 서술하였다.

• 한국소음진동공학회논문집
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• 제13권6호
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• pp.452-459
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• 2003

The characteristics of fluid-elastic instability and effects of turbulent excitations for the KSNP steam generator tubes were investigated numerically. The information for the thermal-hydraulic data of the steam generator has been obtained by using the ATHOS3-MOD1 code and the flow-induced vibration(FIV) analysis has been conducted by using the PIAT(program for Integrity assessment of SG tube) code. The KSNP steam generator has the concentrated plugging zone at the vicinity of the stay cylinder inside the SG. To investigate the cause of the concentrated tube plugging zone, the FIV analysis has been performed for various column and row number of the steam generator tubes. From the results of FIV analysis the stability ratio due to the fluid-elastic instability and vibrational amplitude due to the turbulent excitation in the concentrated plugged zone have a trend of larger values than those of the outer concentrated tube Plugging zone.

• Asian Pacific Journal of Cancer Prevention
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• 제17권6호
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• pp.2989-2993
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• 2016

The commonest cancer in Egyptian females occurs in the breast cfDNA is a non-invasive marker for tumor detetion and prognostic assessment in many types of cancer including breast cancer. This study aimed to assess the role of cfDNA and its fragmentation pattern in breast cancer prognosis and treatment response. Forty female patients with malignant breast tumors and a comparable group of healthy blood donors were enrolled prospectively. cfDNA levels and fragmentation patterns were investigated after cfDNA extraction, gel electrophoresis and gel analysis. The percentage of breast cancer patients positive for cfDNA (92.5%) was significantly higher than that of controls (55%). Also, mean concentration of cfDNA was significantly higher than in the control group (P<0.05). Most Her-2 positive patients had long cfDNA fragments, this being significant as compared to Her-2 negative patients (P<0.05). Metastasis was also positively linked to significantly higher cfDNA (P<0.05) and the mean cfDNA integrity index was significantly higher in non-responders compared to treatment responders (P<0.05). In conclusion, both qualitative and quantitative aspects of cfDNA and its different fragments in breast cancer patients could be related to prognosis, metastasis and treatment response. Long cfDNA fragments could be particularly useful for prediction purposes.

• Structural Engineering and Mechanics
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• 제72권1호
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• pp.31-41
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• 2019

Structural integrity assessment of piping components is of paramount important for remaining life prediction, residual strength evaluation and for in-service inspection planning. For accurate prediction of these, a reliable fracture parameter is essential. One of the fracture parameters is stress intensity factor (SIF), which is generally preferred for high strength materials, can be evaluated by using linear elastic fracture mechanics principles. To employ available analytical and numerical procedures for fracture analysis of piping components, it takes considerable amount of time and effort. In view of this, an alternative approach to analytical and finite element analysis, a model based on relevance vector machine (RVM) is developed to predict SIF of part through crack of a piping component under fatigue loading. RVM is based on probabilistic approach and regression and it is established based on Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Model for SIF prediction is developed by using MATLAB software wherein 70% of the data has been used for the development of RVM model and rest of the data is used for validation. The predicted SIF is found to be in good agreement with the corresponding analytical solution, and can be used for damage tolerant analysis of structural components.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3298-3313
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• 2021

The objective of this study is to estimate the occurrence probabilities of severe accident phenomena based on a fuzzy elicitation technique. Normally, it is difficult to determine these probabilities due to the lack of information on severe accident progression and the highly uncertain values currently in use. In this case, fuzzy set theory (FST) can be best exploited. First, questions were devised for expert elicitation on technical issues of severe accident phenomena. To deal with ambiguities and the imprecision of previously developed (reference) probabilities, fuzzy aggregation methods based on FST were employed to derive the occurrence probabilities of severe accidents via four phases: 1) choosing experts, 2) quantifying weighting factors for the experts, 3) aggregating the experts' opinions, and 4) defuzzifying the fuzzy numbers. In this way, this study obtained expert elicitation results in the form of updated occurrence probabilities of severe accident phenomena in the OPR-1000 plant, after which the differences between the reference probabilities and the newly acquired probabilities using fuzzy aggregation were compared, with the advantages of the fuzzy technique over other approaches explained. Lastly, the impact of applying the updated severe accident probabilities on containment integrity was quantitatively investigated in a Level 2 PSA model.

• Nuclear Engineering and Technology
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• 제51권6호
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• pp.1658-1668
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• 2019

Nuclear power generates a large portion of the energy used today and plays an important role in energy development. To ensure safe nuclear power generation, it is essential to conduct an accurate analysis of reactor structural integrity. Accordingly, in this study, a methodology for obtaining accurate structural responses to the combined seismic and reactor coolant loads existing prior to the shutdown of a nuclear reactor is proposed. By applying the proposed analysis method to the reactor vessel internals, it is possible to derive the seismic responses considering the influence of the hydraulic loads present during operation for the first time. The validity of the proposed methodology is confirmed in this research by using the finite element method to conduct seismic and hydraulic load analyses of the advanced APR1400 1400 MWe power reactor, one of the commercial reactors. The structural responses to the combined applied loads are obtained using displacement-based and stress-based superposition methods. The safety of the subject nuclear reactor is then confirmed by analyzing the design margin according to the American Society for Mechanical Engineers (ASME) evaluation criteria, demonstrating the promise of the proposed analysis method.

• Journal of Yeungnam Medical Science
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• 제36권3호
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• pp.183-191
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• 2019

Some patients with type 1 and type 2 diabetes mellitus (DM) present with cognitive dysfunctions. The pathophysiology underlying this complication is not well understood. Type 1 DM has been associated with a decrease in the speed of information processing, psychomotor efficiency, attention, mental flexibility, and visual perception. Longitudinal epidemiological studies of type 1 DM have indicated that chronic hyperglycemia and microvascular disease, rather than repeated severe hypoglycemia, are associated with the pathogenesis of DM-related cognitive dysfunction. However, severe hypoglycemic episodes may contribute to cognitive dysfunction in high-risk patients with DM. Type 2 DM has been associated with memory deficits, decreased psychomotor speed, and reduced frontal lobe/executive function. In type 2 DM, chronic hyperglycemia, long duration of DM, presence of vascular risk factors (e.g., hypertension and obesity), and microvascular and macrovascular complications are associated with the increased risk of developing cognitive dysfunction. The pathophysiology of cognitive dysfunction in individuals with DM include the following: (1) role of hyperglycemia, (2) role of vascular disease, (3) role of hypoglycemia, and (4) role of insulin resistance and amyloid. Recently, some investigators have proposed that type 3 DM is correlated to sporadic Alzheimer's disease. The molecular and biochemical consequences of insulin and insulin-like growth factor resistance in the brain compromise neuronal survival, energy production, gene expression, plasticity, and white matter integrity. If patients claim that their performance is worsening or if they ask about the effects of DM on functioning, screening and assessment are recommended.

• Journal of Microbiology and Biotechnology
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• 제32권2호
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• pp.212-219
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• 2022

Recently, the efficacy of probiotics in treatment of neurodegenerative disorders has been reported in animal and clinical studies. Here, we assessed the effects of Bacillus coagulans JA845 in counteracting the symptoms of D-galactose (D-gal)/AlCl₃-induced Alzheimer's disease (AD) in a mice model through behavioral test, histological assessment and biochemical analysis. Ten weeks of pre-treatment with B. coagulans JA845 prevented cognitive decline, attenuated hippocampal lesion and protected neuronal integrity, which demonstrated the neuroprotective features of B. coagulans JA845 in vivo. We also found that supplementation of B. coagulans JA845 alleviated amyloid-beta deposits and hyperphosphorylated tau in hippocampus of D-gal/AlCl₃-induced AD model mice. Furthermore, B. coagulans JA845 administration attenuated oxidative stress and decreased serum concentration of inflammatory cytokines by regulating the Nrf2/HO-1 and MyD88/TRAF6/NF-κB pathway. Our results demonstrated for the first time that B. coagulans has the potential to help prevent cognitive decline and might be a novel therapeutic approach for the treatment of neurodegenerative diseases.

• Smart Structures and Systems
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• 제30권1호
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.