• Journal of the Korean Chemical Society
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• v.38 no.7
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• pp.502-508
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• 1994

The measurement of trace amounts of uranium(VI) and thorium(VI) in the solutions containing high concentration of dissolved salts was carried out. The procedure using reversed phase liquid chromatography with trace enrichment techniques has been developed to cope with the high salt content of the samples. 2 ml of sample were passed through a small C_{18}$ reversed phase enrichment column with ${\alpha}$-HIBA eluent (0.11 M, pH 5.5) where the uranium and thorium were separated from other constituents and concentrated. The uranium and thorium were then backflushed from the column onto a deactivated C_{18}$ reversed phase analytical column where furthe separation was achieved with a mixed eluent (pH3.0, 0.17M ${\alpha}$-HIBA/0.0038 M 1-pentanesulfonate). The separated species were determined spectrophotometrically by postcolumn reaction with Arsenazo III, the chromogenic reagent. Detection limits were found within 1 ppb range for both species.

• Imaging Science in Dentistry
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• v.32 no.4
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• pp.213-219
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• 2002

Purpose : Computed radiography (CR) has been used in cephalometric radiography and many studies have been carried out to improve image quality using various digital enhancement and filtering techniques, During CR image acquisition, the frequency rank and type affect to the image quality. The aim of this study was to compare the diagnostic quality of conventional cephalometric radiographs to those of computed radiography. Materials and Methods : The diagnostic quality of conventional cephalometric radiographs (MO) and their digital image counterparts were compared, and at the same time, six modalities (M1-M6) of spatial frequency-processed digital images were compared by evaluating the reproducibility of 23 cephalometric landmark locations. Reproducibility was defined as an observer's deviation (in mm) from the mean between all observers. Results and Conclusion: In comparison with the conventional cephalometric radiograph (MO), Ml showed statistically significant differences in 8 locations, M2 in 9, M3 12, M4 in 7, M5 in 12, and M6 showed significant differences in 14 of 23 landmark locations (p < 0.05). The number of reproducible landmarks that each modality possesses were 7 in M6, 6 in M5, 5 in M3, 4 in M4, 3 in M2, 2 in Ml, and 1 location in MO. The image modality that observers selected as having the best image quality was M5.

• Korean Journal of Pharmacognosy
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• v.36 no.3 s.142
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• pp.186-190
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• 2005

Searching for inhibitors of lipopolysaccharide (LPS)-induced IL-6 (Interleukin-6) production from medicinal herbs, we isolated two active compounds though bioactivity-guided fractionation from the methanol extract of Chrysanthemum indicum L.. They were determined as kikkanol F monoacetate (1) and 5-hydroxy-6,7,3',4'-tetramethoxyflavone (2) by means of spectroscopy techniques such as NMR and MS. The compound 1 and 2 inhibited LPS-induced IL-6 production in the PAW264.7 cells with $IC_{50}$ value of $47\;{\mu}g/ml$ and $27\;{\mu}g/ml$, respectively.

• Journal of Life Science
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• v.17 no.3 s.83
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• pp.407-411
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• 2007

Regulation of ${\beta}-xylosidase$ synthesis in Paenibacillus sp. DC-22 was studied to optimize the enzyme production. ${\beta}-Xylosidase$ synthesis of the Paenibacillus sp. DG-22 was observed to be regulated by carbon sources present in culture media. The synthesis of ${\beta}-xylosidase$ was induced by xylan and methyl ${\beta}-D-xylopyranoside$ (${\beta}MeXyl$) but slightly repressed by readily metabolizable monosaccharides. ${\beta}MeXyl$ was found to be the best substrate for the induction of ${\beta}$-xylosidase and the most effective induction was obtained at a concentration of 10 mg/ml. ${\beta}-Xylosidase$ production showed a cell growth associated profile with the maximum amount formed during the late exponential phase of growth. The presence of glucose and xylose decreased the level of ${\beta}-xylosidase$ activity indicating that its production was subjected to a form of carbon catabolite repression. SDS-PAGE and zymogram techniques demonstrated the induction by ${\beta}MeXyl$ and revealed the presence of one ${\beta}-xylosidase$ of approximately 80 kDa.

• Journal of Microbiology and Biotechnology
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• v.29 no.2
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• pp.274-282
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• 2019

Mercury-resistant ($Hg^R$) bacteria were isolated from heavy metal polluted wastewater and soil collected near to tanneries of district Kasur, Pakistan. Bacterial isolates AZ-1, AZ-2 and AZ-3 showed resistance up to $40{\mu}g/ml$ against mercuric chloride ($HgCl_2$). 16S rDNA ribotyping and phylogenetic analysis were performed for the characterization of selected isolates as Bacillus sp. AZ-1 (KT270477), Bacillus cereus AZ-2 (KT270478) and Bacillus cereus AZ-3 (KT270479). Phylogenetic relationship on the basis of merA nucleotide sequence confirmed 51-100% homology with the corresponding region of the merA gene of already reported mercury-resistant Gram-positive bacteria. The merE gene involved in the transportation of elemental mercury ($Hg^0$) via cell membrane was cloned for the first time into pHLV vector and transformed in overexpressed C43(DE3) E. coli cells. The recombinant plasmid (pHLMerE) was expressed and the native MerE protein was obtained after thrombin cleavage by size exclusion chromatography (SEC). The purification of fusion/recombinant and native protein MerE by Ni-NTA column, dialysis and fast protein liquid chromatography (FPLC/SEC) involved unfolding/refolding techniques. A small-scale reservoir of wastewater containing $30{\mu}g/ml$ of $HgCl_2$ was designed to check the detoxification ability of selected strains. It resulted in 83% detoxification of mercury by B. cereus AZ-2 and B. cereus AZ-3, and 76% detoxification by Bacillus sp. AZ-1 respectively (p < 0.05).

• Journal of Microbiology and Biotechnology
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• v.31 no.12
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• pp.1656-1666
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• 2021

Dental pathogens lead to chronic diseases like periodontitis, which causes loss of teeth. Here, we examined the plausible antibacterial efficacy of copper nanoparticles (CuNPs) synthesized using Cupressus macrocarpa extract (CME) against periodontitis-causing bacteria. The antimicrobial properties of CME-CuNPs were then assessed against oral microbes (M. luteus. B. subtilis, P. aerioginosa) that cause periodontal disease and were identified using morphological/ biochemical analysis, and 16S-rRNA techniques. The CME-CuNPs were characterized, and accordingly, the peak found at 577 nm using UV-Vis spectrometer showed the formation of stable CME-CuNPs. Also, the results revealed the formation of spherical and oblong monodispersed CME-CuNPs with sizes ranged from 11.3 to 22.4 nm. The FTIR analysis suggested that the CME contains reducing agents that consequently had a role in Cu reduction and CME-CuNP formation. Furthermore, the CME-CuNPs exhibited potent antimicrobial efficacy against different isolates which was superior to the reported values in literature. The antibacterial efficacy of CME-CuNPs on oral bacteria was compared to the synergistic solution of clindamycin with CME-CuNPs. The solution exhibited a superior capacity to prevent bacterial growth. Minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and fractional inhibitory concentration (FIC) of CME-CuNPs with clindamycin recorded against the selected periodontal disease-causing microorganisms were observed between the range of 2.6-3.6 ㎍/ml, 4-5 ㎍/ml and 0.312-0.5, respectively. Finally, the synergistic antimicrobial efficacy exhibited by CME-CuNPs with clindamycin against the tested strains could be useful for the future development of more effective treatments to control dental diseases.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.305-307
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• 2021

Alzheimer's Disease (AD) is a cognitive disorder characterized by memory impairment that can be assessed at early stages based on administering clinical tests. However, the AD pathophysiological mechanism is still poorly understood due to the difficulty of distinguishing different levels of AD severity, even using a variety of brain modalities. Therefore, in this study, we present a hybrid EEG-fNIRS modalities to compensate for each other's weaknesses with the help of Machine Learning (ML) techniques for classifying four subject groups, including healthy controls (HC) and three distinguishable groups of AD levels. A concurrent EEF-fNIRS setup was used to record the data from 41 subjects during Oddball and 1-back tasks. We employed both a traditional neural network (NN) and a CNN-LSTM hybrid model for fNIRS and EEG, respectively. The final prediction was then obtained by using majority voting of those models. Classification results indicated that the hybrid EEG-fNIRS feature set achieved a higher accuracy (71.4%) by combining their complementary properties, compared to using EEG (67.9%) or fNIRS alone (68.9%). These findings demonstrate the potential of an EEG-fNIRS hybridization technique coupled with ML-based approaches for further AD studies.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.319-326
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• 2024

Construction projects account for a significant proportion of workplace hazards globally. While construction cost reports typically emphasize direct accident costs such as treatment expenses, nursing care costs, or disability benefits, indirect factors like work interruption loss costs or consolation costs are frequently overlooked, because it is relatively difficult to estimate those factors in advance. Recognizing and accurately estimating the indirect costs factors associated with construction accidents would not only shed light on the monetary impact these incidents have on overall project costs but also would enable to estimate the total accident cost in advance. The current study seeks to identify factors influencing indirect costs, which ultimately govern the total accident cost, through a data mining approach. A survey was conducted in domestic construction companies, resulting in a dataset of 1038 accident records collected from construction sites. First, statistical analysis was performed to uncover characteristics and patterns of factors affecting construction accident costs from both direct and indirect perspectives. Later, this study proposes four distinct machine learning (ML) models, comparing their performances in predicting the total accident cost (including indirect costs) in advance. Additionally, this research sheds light on an important issue in construction data analysis, which is the scarcity of data in a particular class, by applying random oversampling and random undersampling techniques. The suggested framework can assist practitioners and management in estimating construction accident costs and identifying the relevant attributes that impact accidents at the construction site for future practices.

• Journal of Embryo Transfer
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• v.26 no.4
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• pp.271-276
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• 2011

This study was focused on improvement of milk production in Mongolian dairy industry by artificial insemination (AI) technology, supported by ODA of KOICA in Republic of Korea. This program was started in January 2009 and it is in $3^{rd}$ years. This manuscript summarized the data especially on estrus synchronization and pregnancy establishment in dairy cows (Holstein) this year. A total of 81 dairy cows from 4 private farms (38 from Undarmal milk and that of 30, 8 and 5 dairy cows from Onjin (Enkhbayer), Jargalant, and BRM School farms respectively) were synchronized with 5 ml Lutalyse (i.m.) in the dump of dairy cows and then estrus was detected 2 to 3 days after $PGF_{2{\alpha}}$ injection. The synchronized dairy cows were inseminated with 0.5 ml dairy frozen semen by conventional artificial insemination (AI) techniques. Pregnancy was diagnosed about 60 days after AI by palpation method. About 96.3% (78/81) of synchronized cows were responded to single $PGF_{2{\alpha}}$ injection. Total 75 over 78 dairy cows (90.1%) inseminated were diagnosed as pregnant. The estrus induction and pregnancy rates were very effective using Lutalyse injection and conventional AI techniques in Mongolian dairy cow. The present results indicated that AI after estrus induction in Mongolian dairy cows could be applied to dairy breeding technology for improving breeding efficiency and milk production of the country.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.531-536
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• 2011

The precise measurement of human emotion is of pivotal importance in the field of emotion science. Based on the perspective of psychoneuroimmunoendocrinology, human emotion is now considered to be measurable by body fluid. The biological molecule cortisol, which is known for the stress hormone, has been widely investigated to help researchers to estimate the stress loaded on human body. Until now, several measurement techniques such as High Performance Liquid Chromatography (HPLC), fluorometric assay, and reverse phase chromatography have been developed. However, since these measurements are expensive, take relatively long time for an operation, and they are not portable, they are not appropriate for POCT (point of care testing). In this paper we demonstrate the performance of a miniaturized-microwave resonant device in the measurement of cortisol. Our method has many advantages in that it requires a small volume of sample, has fast response time, is easy to operate and needs no labeling process. Besides, it will shed a light on the measurement techniques for emotion science.