• Applied Biological Chemistry
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• v.39 no.6
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• pp.494-500
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• 1996

Uptake of hen metal ions by water dropwort (Oenanthe stolonifera DC.) and its cadmium-binding protein were studied to probe for good method to remove heavy metal contaminants from environments. The plant was cultured in the culture medium (pH 7.0) containing the various concentrations of $Cd^{2+}$, $Cr^{3+}$ or $Pb^{2+}$, for 3 and 7 days. The residual heavy metals deposited in roots linearly increased as the metal ions concentration increased up to 17 ppm for $Cd^{2+}$, 20 ppm for $Cr^{3+}$ and 50 ppm for $Pb^{2+}$. Above these concentrations, the plant growth was inhibited and the uptake rates of the metal ions decreased. The heavy metals absorbed by the plant were mostly deposited in roots. In particular, the residual concentration of lead in roots was about four times higher than those of cadmium and chromium. When cultured in the medium containing 20 ppm of each metal ion, 80% of cadmium, 90% of cromium and 96% of lead were deposited in roots out of the total residual metal ions in the plant. These values correspond to 6.1 mg of cadmium, 5.2 mg of chromium and 23.6 mg of lead per one gram of roots tissue on a dry weight basis. A cadmium-binding protein was partially purified by extraction, gel filtration and DEAE-Cellulose chromatography from water dropworts that was grown in the medium containing 20 ppm $Cd^{2+}$. The purified protein was a single band on SDS- and non-denaturing- polyacrylamide gel electrophoresis. Its molecular mass was estimated to be ca. 5,000 dalton by gel filteration. Analysis of amino acid composition of the protein indicated that it had a typical amino acid composition of heavy metal-binding protein in that it contained 27% of acidic amino acids and 9.9% of cysteine. However, it is likely that the protein is a new plant metal-binding protein, since its amino acid composition is somewhat different from those of phytochelatins that have been known so far.

• Tuberculosis and Respiratory Diseases
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• v.40 no.6
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• pp.653-658
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• 1993

Background: Recent advancement of molecular genetics has revealed that malignant transformation of a cell may be a complex multistep process and this process is grouped, in general, into two distinct categories, activation of protooncogenes and inactivation of tumor suppressor genes. This study was focused on the mutation of p53 tumor suppressor gene, because p53 gene mutation is now generally accepted to be one of the most frequent genetic changes in a variety of human cancers. Although lung cancer is one of the common cancers in Korea, the genetic change in the carcinogenesis process is not yet known clearly. To investigate the role of p53 gene mutation in lung cancer, we examined the mutations of exon 4-8 of the p53 gene in humna lung cancer cell lines, because most of the mutations of p53 gene have been reported to develop in exon 4-8. Method: Genomic DNA was obtained by the digestion of proteinase K and the extraction by phenol-chloroform-ethanol method from two human pulmonary adenocarcinoma cell lines, PC-9 and PC-14, and one human small cell lung cancer cell line, H69. To detect the mutations of exon 4-8 of the p53 gene, polymerase chain reaction single-strand conformation polymorphism(PCR-SSCP) analysis was performed with the DNA extracted from the cells. Results: The mutation of p53 gene was present in all three cell lines tested. In PC-9, PC-14 and H69, the altered mobility was detected in exon 7, 7 and 5, respectively. Conclusion: These results suggest that p53 gene mutation plays an important role in certain steps of the carcinogenesis of human non-small cell and small cell lung cancer.

• Journal of Periodontal and Implant Science
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• v.35 no.3
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• pp.661-674
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• 2005

The purpose of this study was to quantify and compare the level of MMP-2, MMP-8 in the healthy, inflammed gingival tissue and inflammed gingival tissue associated with type 2 DM. We investigate whether expression of MMP-2, MMP-8 is increased by chronic periodontitis associated with type 2 DM. Gingival tissue samples were obtained during periodontal surgery or tooth extraction. Based on patient's systemic condition & clinical criteria of gingiva, each gingival samples were divided into three groups. Group l(n=8) is clinically healthy gingiva without bleeding and no evidence of bone resorption or periodontal pockets, obtained from 8 systemically healthy patients. Group 2(n=8) is inflammed gingiva from patients with chronic periodontitis. Group 3(n=8) is inflammed gingiva from type 2 diabetic patients with chronic periodontitis. Tissue samples were prepared and analyzed by Western blotting. The quantification of MMP-2, MMP-8 was performed using a densitometer and statistically analyzed by ANOVA. MMP-2, MMP-8 was expressed in all samples including healthy gingiva and increased in group 3 compared to group 1 and 2, and showed that significant variation was observed between group 1 & 3 in MMP-8 results. In conclusion, this study demonstrated that human gingival tissue with chronic periodontitis associated to type 2 diabetes showed slightly elevated MMP-2, MMP-8 levels compared to healthy gingiva and non-diabetic inflamed gingiva.

• Proceedings of the Membrane Society of Korea Conference
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• 1999.07a
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• pp.39-42
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• 1999

Perfluoropolymers represent the ultimate resistance to hostile chemical environments and high service temperature, attributed to the presence of fluorine in the polymer backbone, i.e. to the high bond energy of C-F and C-C bonds of fluorocarbons. Copolymers of Tetrafluoroethylene (TEE) and 2, 2, 4Trifluoro-5Trifluorometoxy- 1, 3Dioxole (TTD), commercially known as HYFLON AD, are amorphous perfluoropolymers with glass transition temperature (Tg)higher than room temperature, showing a thermal decomposition temperature exceeding 40$0^{\circ}C$. These polymer systems are highly soluble in fluorinated solvents, with low solution viscosities. This property allows the preparation of self-supported and composite membranes with desired membrane thickness. Symmetric and asymmetric perfluoropolymer membranes, made with HYFLON AD, have been prepared and evaluated. Porous and not porous symmetric membranes have been obtained by solvent evaporation with various processing conditions. Asymmetric membranes have been prepared by th wet phase inversion method. Measure of contact angle to distilled water have been carried out. Figure 1 compares experimental results with those of other commercial membranes. Contact angles of about 120$^{\circ}$for our amorphous perfluoropolymer membranes demonstrate that they posses a high hydrophobic character. Measure of contact angles to hexandecane have been also carried out to evaluate the organophobic character. Rsults are reported in Figure 2. The observed strong organophobicity leads to excellent fouling resistance and inertness. Porous membranes with pore size between 30 and 80 nanometers have shown no permeation to water at pressures as high as 10 bars. However high permeation to gases, such as O2, N2 and CO2, and no selectivities were observed. Considering the porous structure of the membrane, this behavior was expected. In consideration of the above properties, possible useful uses in th field of gas- liquid separations are envisaged for these membranes. A particularly promising application is in the field of membrane contactors, equipments in which membranes are used to improve mass transfer coefficients in respect to traditional extraction and absorption processes. Gas permeation properties have been evaluated for asymmetric membranes and composite symmetric ones. Experimental permselectivity values, obtained at different pressure differences, to various single gases are reported in Tab. 1, 2 and 3. Experimental data have been compared with literature data obtained with membranes made with different amorphous perfluoropolymer systems, such as copolymers of Perfluoro2, 2dimethyl dioxole (PDD) and Tetrafluorethylene, commercialized by the Du Pont Company with the trade name of Teflon AF. An interesting linear relationship between permeability and the glass transition temperature of the polymer constituting the membrane has been observed. Results are descussed in terms of polymer chain structure, which affects the presence of voids at molecular scale and their size distribution. Molecular Dyanmics studies are in progress in order to support the understanding of these results. A modified Theodoru- Suter method provided by the Amorphous Cell module of InsightII/Discover was used to determine the chain packing. A completely amorphous polymer box of about 3.5 nm was considered. Last but not least the use of amorphous perfluoropolymer membranes appears to be ideal when separation processes have to be performed in hostile environments, i.e. high temperatures and aggressive non-aqueous media, such as chemicals and solvents. In these cases Hyflon AD membranes can exploit the outstanding resistance of perfluoropolymers.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Korean Journal of Poultry Science
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• v.46 no.3
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• pp.137-154
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• 2019

This study was conducted to develop and compare Samgyetang broth from extract of pre-treated chicken feet. Chicken feet were subjected to non-heating (control), heating at $70^{\circ}C$ for 12 h in a hot air dryer, and heating at $180^{\circ}C$ for 1 h in an oven. The heat-treated chicken feet were extracted at $121^{\circ}C$ for 1 h and 2 h, respectively. The extract was placed in a pouch with whole chicken carcass ($470{\pm}10g$). The sealed Samgyetang retort was made according to the industrial method. The pH of the extract from preheated chicken feet was lower than that extracted from fresh chicken feet. The Thiobarbituric Acid Reactive Substances (TBARS) value of the preheated chicken feet extract was significantly lower (P<0.05) than that of fresh chicken feet extract, but there were no significant differences among the broths. As the extraction time increased, the pH and TBARS value decreased in the extract (P<0.05) but increased in the broth (P<0.05). According to the sensory evaluation test, the extract from 1 h hot air heating and drying was significantly better in appearance, aroma, and overall preference than the other treatments (P<0.05). The GC-MS results showed that benzaldehyde and benzothiazole, which are widely known to give meat and nuts flavor, were detected in those treatments (P<0.05). The Samgyetang broths prepared from 1 h hot air heating and drying extract were significantly higher in the overall acceptability according to the sensory test (P<0.05). In summary, the quality of retort Samgyetang broth can be improved by adding chicken feet extract which is subjected to heating and drying for 1 h.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.34 no.3
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• pp.27-54
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• 2021

Objectives : This review was conducted to validate the effectiveness and safety of herbal medicine combined with conventional therapy for rosacea. Methods : Randomized controlled trials(RCTs) reporting the effects of herbal medicine treatment on rosacea were searched through eight electronic databases from 2016 to March 17, 2020. This study collection and data extraction were performed by two independent reviews. The Cochrane risk-of-bias tool was used for the evaluation of the risk of bias in all included RCTs. Mean differences(MD) and Risk ratio(RR) of 95% Confidence intervals(Cls) were calculated and data synthesis was conducted using Review Manager(RevMan, ver.5.4) Results : Eighteen RCTs were included and all trials compared the combined therapy of herbal medicine with conventional western therapy to conventional therapy alone. The effective rate of the combination of herbal medicine with western medicine(RR 1.20, 95% CI : 1.13-1.28, p<0.00001, I²=0%), the effective rate of the combination of herbal medicine with laser-based therapy(RR 1.12, 95% CI : 1.04-1.21, p=0.004, I²=18%) and the effective rate of the combination treatment group using herbal medicine, western medicine and external drugs were all statistically higher that of the control group(RR 1.19, 95% CI : 1.11-1.28, p<0.00001, I²=0%). The score of non transient erythema(MD -0.36, 95% CI : -1.01 0.29, p=0.27, I²=93%), flushing(MD -0.69, 95% CI : -0.97, 0.41, p<0.00001, I²=32%), papules or pustules(MD 0.10, 95% CI : -0.15, 0.35 p=0.44, I²=0%) were also seen in the herbal medicine and western medicine combination group. The overall risk of bias of the included studies was some concerns. No serious adverse effects were observed. Conclusions : This review found the safety and effectiveness of the combined therapy of herbal medicine with conventional western therapy for rosacea.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.85-103
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• 2023

The in-situ remediation of a solidified stratum containing a large amount of fine-texture material like clay or organic matter in contaminated soil faces limitations such as increased remediation cost resulting from decreased purification efficiency. Even if the soil conditions are good, remediation generally requires a long time to complete because of non-uniform soil properties and low permeability. This study assessed the remediation effect and evaluated the field applicability of a methodology that combines pneumatic fracturing, vacuum extraction, and plasma blasting (the PPV method) to improve the limitations facing existing underground remediation methods. For comparison, underground remediation was performed over 80 days using the experimental PPV method and chemical oxidation (the control method). The control group showed no decrease in the degree of contamination due to the poor delivery of the soil remediation agent, whereas the PPV method clearly reduced the degree of contamination during the remediation period. Remediation effect, as assessed by the reduction of the highest TPH (Total Petroleum Hydrocarbons) concentration by distance from the injection well, was uncleared in the control group, whereas the PPV method showed a remediation effect of 62.6% within a 1 m radius of the injection well radius, 90.1% within 1.1~2.0 m, and 92.1% within 2.1~3.0 m. When evaluating the remediation efficiency by considering the average rate of TPH concentration reduction by distance from the injection well, the control group was not clear; in contrast, the PPV method showed 53.6% remediation effect within 1 m of the injection well, 82.4% within 1.1~2.0 m, and 68.7% within 2.1~3.0 m. Both ways of considering purification efficiency (based on changes in TPH maximum and average contamination concentration) found the PPV method to increase the remediation effect by 149.0~184.8% compared with the control group; its average increase in remediation effect was ~167%. The time taken to reduce contamination by 80% of the initial concentration was evaluated by deriving a correlation equation through analysis of the TPH concentration: the PPV method could reduce the purification time by 184.4% compared with chemical oxidation. However, the present evaluation of a single site cannot be equally applied to all strata, so additional research is necessary to explore more clearly the proposed method's effect.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.