• Metals and materials international
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• v.24 no.6
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• pp.1193-1201
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• 2018

Dilatometry is a useful technique to obtain experimental data concerning transformation. In this paper, a dilation conversional model was established to calculate carbides fraction in AISI H13 hot-work tool steel based on the measured length changes. After carbides precipitation, the alloy contents in the matrix changed. In the usual models, the content of carbon atoms after precipitation is considered as the only element that affects the lattice constant and the content of the alloy elements such as Cr, Mo, Mn, V are often ignored. In the model introduced in this paper, the alloying elements (Cr, Mo, Mn, V) changes caused by carbides precipitation are incorporated. The carbides were identified using scanning electron microscope and transmission electron microscope. The relationship between lattice constant of carbides and temperature are measured by high-temperature X-ray diffraction. The results indicate that the carbides observed in all specimens cooled at different rates are V-rich MC and Cr-rich $M_{23}C_6$, and most of them are V-rich MC, only very few are Cr-rich $M_{23}C_6$. The model including the effects of substitutional alloying elements shows a good improvement on carbides fraction predictions. In addition, lower cooling rate advances the carbides precipitation for AISI H13 specimens. The results between experiments and mathematical model agree well.

• Restorative Dentistry and Endodontics
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• v.43 no.4
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• pp.40.1-40.10
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• 2018

Objectives: This study evaluated the microtensile bond strength (${\mu}TBS$) of polymer-ceramic and indirect composite resin with 3 classes of resin cements. Materials and Methods: Two computer-aided design/computer-aided manufacturing (CAD/CAM)-fabricated polymer-ceramics (Enamic [ENA; Vita] and Lava Ultimate [LAV; 3M ESPE]) and a laboratory indirect composite resin (Gradia [GRA; GC Corp.]) were equally divided into 6 groups (n = 18) with 3 classes of resin cements: Variolink N (VAR; Vivadent), RelyX U200 (RXU; 3M ESPE), and Panavia F2 (PAN; Kuraray). The ${\mu}TBS$ values were compared between groups by 2-way analysis of variance and the post hoc Tamhane test (${\alpha}=0.05$). Results: Restorative materials and resin cements significantly influenced ${\mu}TBS$ (p < 0.05). In the GRA group, the highest ${\mu}TBS$ was found with RXU ($27.40{\pm}5.39N$) and the lowest with VAR ($13.54{\pm}6.04N$) (p < 0.05). Similar trends were observed in the ENA group. In the LAV group, the highest ${\mu}TBS$ was observed with VAR ($27.45{\pm}5.84N$) and the lowest with PAN ($10.67{\pm}4.37N$) (p < 0.05). PAN had comparable results to those of ENA and GRA, whereas the ${\mu}TBS$ values were significantly lower with LAV (p = 0.001). The highest bond strength of RXU was found with GRA ($27.40{\pm}5.39N$, p = 0.001). PAN showed the lowest ${\mu}TBS$ with LAV ($10.67{\pm}4.37N$; p < 0.001). Conclusions: When applied according to the manufacturers' recommendations, the ${\mu}TBS$ of polymer-ceramic CAD/CAM materials and indirect composites is influenced by the luting cements.

• Journal of Conservation Science
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• v.35 no.2
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• pp.145-152
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• 2019

The metal-manufacturing method and smelting temperature of ancient metal-production processes have been studied by analyzing the principal elements and microstructures of slag. However, the microstructure of slag varies according to the solidification cooling rate and types and relative amounts of various oxides contained within the smelting materials. Hence, there is a need for accurate analysis methods that allow slag to be distinguished by more than its composition or microstructure. In this study, the microstructures of slag discharged as a result of smelting iron sands collected from Pohang and Gyeongju, as well as the slag excavated from the Ungyo site in Wanju, were analyzed by using metalloscopy, scanning election microscopy-energy dispersine X-ray spectroscopy(SEM-EDS) and wavelength dispersive X-ray fluorenscence(WD-XRF). Furthermore, the microcrystals were accurately characterized by performing Raman micro-spectroscopy, which is a technique that can be used to identify the microcrystals of slags. SEM-EDS analysis of Pohang slag indicated that its white polygonal crystals could be Magnetite; however, Raman micro-spectroscopy revealed that these crystals were actually $ulv{\ddot{o}}spinel$. Raman micro-spectroscopy and SEM-EDS were also used to verify that the coarse white dendritic structures observed in the Gyeongju-slag were $W{\ddot{u}}stites$. Additionally, the Wanju slag was observed to have a glassy matrix, which was confirmed by Raman micro-spectroscopy to be Augite. Thus, we have demonstrated that Raman micro-spectroscopy can accurately identify slag microcrystals, which are otherwise difficult to distinguish as solely based on their chemical composition and crystal morphology. Therefore, we conclude that it has excellent potential as a slag analysis technique.

• Laboraroty Animal Research
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• v.33 no.1
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• pp.40-47
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• 2017

HemoHIM, herbal preparation has designed for immune system recovery. We investigated the anti-inflammatory effect of HemoHIM on cigarette smoke (CS) and lipopolysaccharide (LPS) induced chronic obstructive pulmonary disease (COPD) mouse model. To induce COPD, C57BL/6 mice were exposed to CS for 1 h per day (eight cigarettes per day) for 4 weeks and intranasally received LPS on day 26. HemoHIM was administrated to mice at a dose of 50 or 100 mg/kg 1h before CS exposure. HemoHIM reduced the inflammatory cell count and levels of tumor necrosis factor receptor (TNF)-${\alpha}$, interleukin (IL)-6 and IL-$1{\beta}$ in the broncho-alveolar lavage fluid (BALF) induced by CS+LPS exposure. HemoHIM decreased the inflammatory cell infiltration in the airway and inhibited the expression of iNOS and MMP-9 and phosphorylation of Erk in lung tissue exposed to CS+LPS. In summary, our results indicate that HemoHIM inhibited a reduction in the lung inflammatory response on CS and LPS induced lung inflammation via the Erk pathway. Therefore, we suggest that HemoHIM has the potential to treat pulmonary inflammatory disease such as COPD.

• Biomedical Science Letters
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• v.27 no.3
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• pp.142-153
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• 2021

Liver fibrosis is a wound-healing response to chronic liver injury, which is caused by the continuous and excess deposition of extracellular matrix (ECM). The aim of this study is to investigate whether Uncaria rhynchophylla water extract (UR) can ameliorate thioacetamide (TAA)-induced liver fibrosis. The liver fibrosis model was induced on C57BL/6 mice by intraperitoneal injection with TAA three times a week for 8 weeks. UR (200 mg/kg) or silymarin (50 mg/kg) was administered orally daily for 8 weeks. Biochemical analyses including AST, ALT, MPO, and Ammonia levels were measured in serum. In the mice liver tissues, western blot and histological staining were analyzed. As a result, UR dramatically reduced the levels in serum AST, ALT, MPO, and Ammonia levels. UR treatment regulated NADPH oxidase factors expression, and antioxidant enzymes except for GPx-1/2 were significantly increased via Nrf2 activation. Furthermore, pro-inflammatory mediators, such as COX-2 and iNOS were markedly suppressed through the inhibition of NF-κB activation. Expressions of ECM-related protein including α-SMA and Collagen I were noticeably decreased. The additional histological evaluation confirmed that hepatocyte damage and collagenous fiber accumulation were attenuated. Taken together, these data suggest that UR possessed hepatoprotective effects in TAA-induced liver fibrosis via the NF-κB inactivation and Nrf2 activation. Therefore, UR may act as a potential therapeutic drug against liver fibrosis.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.599-610
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• 2021

Early detection of small concrete crack or reinforcement corrosion is necessary for Structural Health Monitoring (SHM). Global vibration based methods are advantageous over local methods because of simple equipment installation and cost efficiency. Among vibration based techniques, FRF based methods are preferred over modal based methods. In this study, a new coupled method using frequency response function (FRF) and proper orthogonal modes (POM) is proposed by using the dynamic characteristic of a damaged beam. For the numerical simulation, wave finite element (WFE), coupled with traditional finite element (FE) method is used for effectively incorporating the damage related information and faster computation. As reported in literature, hybrid combination of wave function based wave finite element method and shape function based finite element method can addresses the mid frequency modelling difficulty as it utilises the advantages of both the methods. It also reduces the dynamic matrix dimension. The algorithms are implemented on a three-dimensional reinforced concrete beam. Damage is modelled and studied for two scenarios, i.e., crack in concrete and rebar corrosion. Single and multiple damage locations with different damage length are also considered. The proposed methodology is found to be very sensitive to both single- and multiple- damage while being computationally efficient at the same time. It is observed that the detection of damage due to corrosion is more challenging than that of concrete crack. The similarity index obtained from the damage parameters shows that it can be a very effective indicator for appropriately indicating initiation of damage in concrete structure in the form of spread corrosion or invisible crack.

• Journal of Animal Science and Technology
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• v.62 no.6
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• pp.884-892
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• 2020

Corticosterone is known as a biological stress index in many species including birds. Feather corticosterone concentration (FCC) has increasingly been used as a measure for chronic stress status in broiler chickens. As sample preparation is the first step of analytical process, different techniques of feather matrix disruption need to be validated for obtaining better result in analysing corticosterone extraction. The current study was a validation of pulverizing the feather by bead beater (BB) and surgical scissors (SS) processing prior to corticosterone extraction in feather of broiler chickens. The type of feather processing prior to the hormone extraction may alter the final output. Thereby, finding a standard method according to laboratory facilities is pivotal. This study carried out to determine the effects of feather pulverization methods on the extraction amount of corticosterone in broiler chickens. Feathers were sampled from four weeks old Ross 308 broiler chickens (n = 12 birds). All broiler chickens were kept under the same environmental condition and had access to feed and water. Feather samples were assigned to one of the following processing methods 1) using a BB for pulverizing and 2) using a SS for chopping into tiny pieces. Each sample was duplicated into two wells during enzyme immunoassay (EIA) analysis to improve the accuracy of the obtained data. The results showed lower standard errors and constant output of FCC by using the BB method compared with the SS method. Overall comparison of FCC showed a significantly higher (p < 0.001) amount of the FCC in the BB compared with the SS. Overall, using the BB method is recommended over the SS method for feather processing due to the ability to homogenize a large number of samples simultaneously, ease of use and greater extraction of feather corticosterone.

• Journal of Ginseng Research
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• v.46 no.1
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• pp.167-174
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• 2022

Background: 20(S)-protopanaxadiol (20(S)-PPD), one of the main active metabolites of ginseng, performs a broad spectrum of anti-tumor effects. Our aims are to search out new strategies to enhance anti-tumor effects of natural products, including 20(S)-PPD. In recent years, fasting has been shown to be multi-functional on tumor progression. Here, the effects of fasting combined with 20(S)-PPD on hepatocellular carcinoma growth, apoptosis, migration, invasion and cell cycle were explored. Methods: CCK-8 assay, trypan blue dye exclusion test, imagings photographed by HoloMonitorTM M4, transwell assay and flow cytometry assay were performed for functional analyses on cell proliferation, morphology, migration, invasion, apoptosis, necrosis and cell cycle. The expressions of genes on protein levels were tested by western blot. Tumor-bearing mice were used to evaluate the effects of intermittent fasting combined with 20(S)-PPD. Results: We firstly confirmed that fasting-mimicking increased the anti-proliferation effect of 20(S)-PPD in human HepG2 cells in vitro. In fasting-mimicking culturing medium, the apoptosis and necrosis induced by 20(S)-PPD increased and more cells were arrested at G0-G1 phase. Meanwhile, invasion and migration of cells were decreased by down-regulating the expressions of matrix metalloproteinase (MMP)-2 and MMP-9 in fasting-mimicking medium. Furthermore, the in vivo study confirmed that intermittent fasting enhanced the tumor growth inhibition of 20(S)-PPD in H22 tumor-bearing mice without obvious side effects. Conclusion: Fasting significantly sensitized HCC cells to 20(S)-PPD in vivo and in vitro. These data indicated that dietary restriction can be one of the potential strategies of chinese medicine or its active metabolites against hepatocellular carcinoma.

• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• Computers and Concrete
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• v.32 no.3
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• pp.327-337
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• 2023

Concrete is the most widely used building material, with various types including high- and ultra-high-strength, reinforced, normal, and lightweight concretes. However, accurately predicting concrete properties is challenging due to the geotechnical design code's requirement for specific characteristics. To overcome this issue, researchers have turned to new technologies like machine learning to develop proper methodologies for concrete specification. In this study, we propose a highly accurate deep learning-based predictive model to investigate the compressive strength (UCS) of lightweight concrete with natural aggregates (pumice). Our model was implemented on a database containing 249 experimental records and revealed that water, cement, water-cement ratio, fine-coarse aggregate, aggregate substitution rate, fine aggregate replacement, and superplasticizer are the most influential covariates on UCS. To validate our model, we trained and tested it on random subsets of the database, and its performance was evaluated using a confusion matrix and receiver operating characteristic (ROC) overall accuracy. The proposed model was compared with widely known machine learning methods such as MLP, SVM, and DT classifiers to assess its capability. In addition, the model was tested on 25 laboratory UCS tests to evaluate its predictability. Our findings showed that the proposed model achieved the highest accuracy (accuracy=0.97, precision=0.97) and the lowest error rate with a high learning rate (R2=0.914), as confirmed by ROC (AUC=0.971), which is higher than other classifiers. Therefore, the proposed method demonstrates a high level of performance and capability for UCS predictions.