• Smart Structures and Systems
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• v.3 no.1
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• pp.23-49
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• 2007

Wavelet transforms are the emerging signal-processing tools for damage identification and time-frequency localization. A small perturbation in a static or dynamic displacement profile could be captured using multi-resolution technique of wavelet analysis. The paper presents the wavelet analysis of damaged linear structural elements using DB4 or BIOR6.8 family of wavelets. Starting with a localized reduction of EI at the mid-span of a simply supported beam, damage modeling is done for a typical steel and reinforced concrete beam element. Rotation and curvature mode shapes are found to be the improved indicators of damage and when these are coupled with wavelet analysis, a clear picture of damage singularity emerges. In the steel beam, the damage is modeled as a rotational spring and for an RC section, moment curvature relationship is used to compute the effective EI. Wavelet analysis is performed for these damage models for displacement, rotation and curvature mode shapes as well as static deformation profiles. It is shown that all the damage indicators like displacement, slope and curvature are magnified under higher modes. A localization scheme with arbitrary location of curvature nodes within a pseudo span is developed for steady state dynamic loads, such that curvature response and damages are maximized and the scheme is numerically tested and proved.

• Computers and Concrete
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• v.16 no.5
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• pp.683-701
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• 2015

When approached using nonlinear finite element (FE) techniques, structural analyses generate, for real RC structures, large complex numerical problems. Damage is a major part of concrete behavior, and the discretization technique is critical to limiting the size of the problem. Based on previous work, the ${\mu}$ damage model has been designed to activate the various damage effects correlated with monotonic and cyclic loading, including unilateral effects. Assumptions are formulated to simplify constitutive relationships while still allowing for a correct description of the main nonlinear effects. After presenting classical 2D finite element applications on structural elements, an enhanced simplified FE description including a damage description and based on the use of multi-fiber beam elements is provided. Improvements to this description are introduced both to prevent dependency on mesh size as damage evolves and to take into account specific phenomena (permanent strains and damping, steel-concrete debonding). Applications on RC structures subjected to cyclic loads are discussed, and results lead to justifying the various concepts and assumptions explained.

• Smart Structures and Systems
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• v.25 no.3
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• pp.285-299
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• 2020

Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2961-2966
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• 2012

Extremely low frequency electro magnetic fields (EMFs) have been classified as possibly carcinogenic to humans by the International Agency for Research on Cancer. An increased number of chromosomal alterations in peripheral lymphocytes are correlated with elevated incidence of cancer. The aim of the present study was to assess occupationally induced chromosomal damage in EMF workers exposed to low levels of radiation. We used conventional metaphase chromosome aberration (CA) analysis and the micronucleus (MN) assay as biological indicators of non ionizing radiation exposure. In the present study totally 70 subjects were selected including 50 exposed and 20 controls. Informed written consent was obtained from all participants and the study was performed in accordance with the Declaration of Helsinki and the approval of the local ethical committee. A higher degree of CA and MN was observed in exposed subjects compared to controls, the frequency of CA being significantly enhanced with long years of exposure (P<0.05). Moreover increase in CA and MN with age was noted in both exposed subjects and controls, but was significantly greater in the former. The results of this study demonstrated that a significant induction of cytogenetic damage in peripheral lymphocytes of workers occupationally exposed to EMFs in electric transformer and distribution stations. In conclusion, our findings suggest that EMFs possess genotoxic capability, as measured by CA and MN assays; CA analysis appeared more sensitive than other cytogenetic end-points. It can be concluded that chronic occupational exposure to EMFs may lead to an increased risk of genetic damage among electrical workers.

• The Korean Journal of Physiology and Pharmacology
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• v.28 no.1
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• pp.1-10
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• 2024

Type 2 diabetes mellitus (T2DM) is characterized by hyperglycemia and dyslipidemia. Carvacrol (CAR) has demonstrated the potential to mitigate dyslipidemia. This study aims to investigate whether CAR can modulate blood glucose and lipid levels in a T2DM rat model by regulating short-chain fatty acids (SCFAs) and the GPR41/43 pathway. The T2DM rat model was induced by a high-fat diet combined with low-dose streptozocin injection and treated with oral CAR and/or mixed antibiotics. Fasting blood glucose, oral glucose tolerance, and insulin tolerance tests were assessed. Serum lipid parameters, hepatic and renal function indicators, tissue morphology, and SCFAs were measured. In vitro, high glucose (HG)-induced IEC-6 cells were treated with CAR, and optimal CAR concentration was determined. HG-induced IEC-6 cells were treated with SCFAs or/and GPR41/43 agonists. CAR significantly reduced blood lipid and glucose levels, improved tissue damage, and increased SCFA levels in feces and GPR41/43 expression in colonic tissues of T2DM rats. CAR also attenuated HG-induced apoptosis of IEC-6 cells and enhanced GPR41/43 expression. Overall, these findings suggest that CAR alleviates blood lipid and glucose abnormalities in T2DM rats by modulating SCFAs and the GPR41/43 pathway.

• Journal of Ginseng Research
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• v.45 no.2
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• pp.295-304
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• 2021

Background: Acute promyelocytic leukemia (APL) is a hematopoietic malignancy driven by promyelocytic leukemia-retinoic acid receptor A (PML-RARA) fusion gene. The therapeutic drugs currently used to treat APL have adverse effects. 20(S)-ginsenoside Rh2 (GRh2) is an anticancer medicine with high effectiveness and low toxicity. However, the underlying anticancer mechanisms of GRh2-induced PML-RARA degradation and apoptosis in human APL cell line (NB4 cells) remain unclear. Methods: Apoptosis-related indicators and PML-RARA expression were determined to investigate the effect of GRh2 on NB4 cells. Z-VAD-FMK, LY294002, and C 87, as inhibitors of caspase, and the phosphatidylinositol 3-kinase (PI3K) and tumor necrosis factor-α (TNF-α) pathways were used to clarify the relationship between GRh2-induced apoptosis and PML-RARA degradation. Results: GRh2 dose- and time-dependently decreased NB4 cell viability. GRh2-induced apoptosis, cell cycle arrest, and caspase3, caspase8, and caspase9 activation in NB4 cells after a 12-hour treatment. GRh2-induced apoptosis in NB4 cells was accompanied by massive production of reactive oxygen species, mitochondrial damage and upregulated Bax/Bcl-2 expression. GRh2 also induced PML/PML-RARA degradation, PML nuclear bodies formation, and activation of the downstream p53 pathway in NB4 cells. Z-VAD-FMK inhibited caspase activation and significantly reversed GRh2-induced apoptosis and PML-RARA degradation. GRh2 also upregulated TNF-α expression and inhibited Akt phosphorylation. LY294002, an inhibitor of the PI3K pathway, enhanced the antitumor effects of GRh2, and C 87, an inhibitor of the TNF-α pathway, reversed NB4 cell viability, and GRh2-mediated apoptosis in a caspase-8-dependent manner. Conclusion: GRh2 induced caspase-dependent PML-RARA degradation and apoptosis in NB4 cells via the Akt/Bax/caspase9 and TNF-α/caspase8 pathways.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.55-62
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• 2023

Recent ransomware attacks employ various techniques and pathways, posing significant challenges in early detection and defense. Consequently, the scale of damage is continually growing. This paper introduces a machine learning-based approach for effective ransomware detection by focusing on file encryption and encryption patterns, which are pivotal functionalities utilized by ransomware. Ransomware is identified by analyzing password behavior and encryption patterns, making it possible to detect specific ransomware variants and new types of ransomware, thereby mitigating ransomware attacks effectively. The proposed machine learning-based encryption behavior detection technique extracts encryption and encryption pattern characteristics and trains them using a machine learning classifier. The final outcome is an ensemble of results from two classifiers. The classifier plays a key role in determining the presence or absence of ransomware, leading to enhanced accuracy. The proposed technique is implemented using the numpy, pandas, and Python's Scikit-Learn library. Evaluation indicators reveal an average accuracy of 94%, precision of 95%, recall rate of 93%, and an F1 score of 95%. These performance results validate the feasibility of ransomware detection through encryption behavior analysis, and further research is encouraged to enhance the technique for proactive ransomware detection.

• Journal of Food Hygiene and Safety
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• v.28 no.2
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• pp.146-151
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• 2013

Perilla frutescens usually dieted in East Asian country such as Korea and Japan. Antioxidant, antiinflammatory and anticancer activities of perilla leaves have been founded. In previous study, we confirmed that caffeic acid, major compound of perilla, was accumulation by sucrose aqueous solution and thus antioxidant effect of perilla was enhanced. In this study, we investigated the protective effect of functional perilla leaves extract (PLE) against tert-butyl hydroperoxide(t-BHP) induced-oxidative hepatotoxicity. The pretreatment with PLE (250, 500 and 1000 mg/kg b.w.) for 5 days before a single dose of t-BHP (i.p.; 0.5 mmol/kg) significantly lowered the serum levels of aspartate aminotransferase, alanine aminotransferase and lactate dehydrogenase dose-dependently. And we confirmed that the indicators of oxidative stress were remarkably reduced in the liver, such as the glutathione contents and malondialdehyde, marker of lipid peroxidation. Pathological histology of the rat livers tissues showed that PLE reduced the hepatocyte degeneration and neutrophilic infiltration of liver induced by t-BHP. These results suggest that functional perilla frutescens has the protective effect of liver against t-BHP-induced oxidative hepatic stress in rats.