• Mass Spectrometry Letters
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• v.12 no.2
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• pp.53-58
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• 2021

Previous in vitro studies have demonstrated that ginsenoside Rc inhibits UGT1A9, but there are no available data to indicate that ginsenoside Rc inhibits UGT1A9 in vivo. The effect of single and repeated intravenous injection of ginsenoside Rc was evaluated on the pharmacokinetics of mycophenolic acid. After injection of ginsenoside Rc (5 mg/kg for one day or 3 mg/kg for five days), 2-mg mycophenolic acid was intravenously injected, and the pharmacokinetics of mycophenolic acid and mycophenolic acid-β-glucuronide were determined. Concentrations of mycophenolic acid and its metabolite from rat plasma were analyzed using a liquid chromatography-triple quadrupole mass spectrometry. Single or repeated pretreatment with ginsenoside Rc had no significant effects on the pharmacokinetics of mycophenolic acid (P > 0.05): The mean difference in maximum plasma concentration (C_max) and area under the concentration-time curve (AUC_inf) were within 0.83- and 0.62-fold, respectively, compared with those in the absence of the ginsenoside Rc. These results indicate that ginsenoside Rc has a negligible effect on the disposition of mycophenolic acid in vivo despite in vitro findings indicating that ginsenoside Rc is a selective UGT1A9 inhibitor. As a result, ginsenoside Rc has little possibility of interacting with drugs that are metabolized by UGT1A9, including mycophenolic acid.

• Clinical Endoscopy
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• v.57 no.4
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• pp.527-533
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• 2024

Background/Aims: Endoscopic ultrasound (EUS)-guided hepaticogastrostomy (EUS-HGS) performed at the intrahepatic bile duct segment 3 (B3) is widely used for biliary drainage. Although performing post-puncture procedures is easier in the intrahepatic bile duct segment 2 (B2) when using a conventional oblique-viewing (OV) EUS scope, this method may cause transesophageal puncture and severe adverse events. We evaluated the safety and efficacy of B2 puncture using a novel OV-EUS scope. Methods: In this single-center retrospective study, we prospectively enrolled and collected data from 45 patients who consecutively underwent EUS-HGS procedures with a novel OV-EUS scope between September 2021 and December 2022 at our cancer center. Results: The technical success rates of B2-EUS-HGS and EUS-HGS were 93.3% (42/45) and 97.8% (44/45), respectively. The early adverse event rate was 8.9% (4/45) with no cases of scope changes or transesophageal punctures. The median procedure time was 13 minutes (range, 5-30). Conclusions: B2-EUS-HGS can be performed safely with the novel EG-740UT (Fujifilm) OV-scope without transesophageal puncture and with a high success rate. B2-EUS-HGS using this novel OV scope may be the preferred strategy for EUS-HGS.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.214-222
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• 2022

Convolutional Neural networks (CNNs) are a category of deep learning networks that have proven very effective in computer vision tasks such as image classification. Notwithstanding, not much has been seen in its use for remote sensing image classification in developing countries. This is majorly due to the scarcity of training data. Recently, transfer learning technique has successfully been used to develop state-of-the art models for remote sensing (RS) image classification tasks using training and testing data from well-known RS data repositories. However, the ability of such model to classify RS test data from a different dataset has not been sufficiently investigated. In this paper, we propose a deep CNN model that can classify RS test data from a dataset different from the training dataset. To achieve our objective, we first, re-trained a ResNet-50 model using EuroSAT, a large-scale RS dataset to develop a base model then we integrated Augmentation and Ensemble learning to improve its generalization ability. We further experimented on the ability of this model to classify a novel dataset (Nig_Images). The final classification results shows that our model achieves a 96% and 80% accuracy on EuroSAT and Nig_Images test data respectively. Adequate knowledge and usage of this framework is expected to encourage research and the usage of deep CNNs for land cover mapping in cases of lack of training data as obtainable in developing countries.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Microbiology and Biotechnology Letters
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• v.52 no.2
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• pp.141-151
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• 2024

Isochrysis sp. is a sea microalga that has become a species of interest because of the extreme lipid content and rapid growth rate of this organism indicating its potential for efficient biofuel production. Using genome sequencing/genome-scale modeling for the prediction of Isochrysis sp. metabolic utilities there is high scope for the identification of essential pathways for the extraction of byproducts of interest at a higher rate. In our work, we design and present iIsochr964, a genome-scale metabolic model of Isochrysis sp. including 4315 reactions, 934 genes, and 1879 metabolites, which are distributed among fourteen compartments. For model validation, experimental culture, and isolation of Isochrysis sp. were performed and biomass values were used for validation of the genome-scale model. OptFlux was instrumental in uncovering several novel metabolites that influence the organism's metabolism by increasing the flux of interacting metabolites, such as Malonyl-CoA, EPA, Protein and others. iIsochr964 provides a compelling resource of metabolic understanding to revolutionize its industrial applications, thereby fostering sustainable development and allowing estimations and simulations of the organism metabolism under varying physiological, chemical, and genetic conditions. It is also useful in principle to provide a systemic view of Isochrysis sp. metabolism, efficiently guiding research and granting context to omics data.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.533-542
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• 2017

In diagnostic radiology, the imaging system has been changed from film/screen to digital system. However, the method for removing scatter radiation such as anti-scatter grid has not kept pace with this change. Therefore, authors have devised the indirect flat panel detector (FPD) system with net-like lead in substrate layer which can remove the scattered radiation. In clinical context, there are many radiographic examinations with angulated incident X-ray. However, our proposed FPD has net-like lead foil so the vertical lead foil to the angulate incident X-ray would have bad effect on its performance. In this study, we identified the effect of vertical/horizontal lead foil component on the novel system's performance and improved the structure of novel system for clinical usage with angulated incident X-ray. Grid exposure factor and image contrast were calculated to investigate various structure of novel system using Monte Carlo simulation software when the incident X-ray was tilted ($0^{\circ}$, $15^{\circ}$, and $30^{\circ}$ from the detector plane). More photons were needed to obtain same image quality in the novel system with vertical lead foil only then the system with horizontal lead foil only. An optimal structure of novel system having different heights of its vertical and horizontal lead foil component showed improved performance compared with the novel system in a previous study. Therefore, the novel system will be useful in a clinical context with the angulated incident X-ray if the height and direction of lead foil in the substrate layer are optimized as the condition of conventional radiography.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.57-68
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• 2017

The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.343-354
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• 2023

Recently, there have been many improvements in general language models using architectures such as GPT-3 proposed by Brown et al. (2020). Nevertheless, training complex models can hardly be done if the number of data is very small. Data augmentation that addressed this problem was more than normal success in image data. Image augmentation technology significantly improves model performance without any additional data or architectural changes (Perez and Wang, 2017). However, applying this technique to textual data has many challenges because the noise to be added is veiled. Thus, we have developed a novel method for performing data augmentation on text data. We divide the data into signals with positive or negative meaning and noise without them, and then perform data augmentation using k-doc augmentation to randomly combine signals and noises from all data to generate new data.

• Journal of Communications and Networks
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• v.11 no.4
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• pp.337-349
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• 2009

In this paper, we introduce a novel mobility model for mobile sinks in which the sinks move towards randomly distributed destinations, where each destination is associated with a mission. The novel mobility model is termed the random mobility with destinations. There have been many studies on mobile sinks; however, they merely support two extreme cases of sink mobility. The first case features the most common and general mobility, with the sinks moving randomly, unpredictably, and inartificially. The other case takes into account mobility only along predefined or determined paths such that the sinks can gather data from sensor nodes with minimum overhead. Unfortunately, these studies for the common mobility and predefined path mobility might not suit for supporting the random mobility with destinations. In order to support random mobility with destination, we propose a new protocol, in which the source nodes send their data to the next movement path of a mobile sink. To implement the proposed protocol, we first present a mechanism for predicting the next movement path of a mobile sink based on its previous movement path. With the information about predicted movement path included in a query packet, we further present a mechanism that source nodes send energy-efficiently their data along the next movement path before arriving of the mobile sink. Last, we present mechanisms for compensating the difference between the predicted movement path and the real movement path and for relaying the delayed data after arriving of the mobile sink on the next movement path, respectively. Simulation results show that the proposed protocol achieves better performance than the existing protocols.

• Mycobiology
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• v.49 no.6
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• pp.582-588
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• 2021

The interaction of mating pheromone and pheromone receptor from the B mating-type locus is the first step in the activation of the mushroom mating signal transduction pathway. The B mating-type locus of Lentinula edodes is composed of Bα and Bβ subloci, each of which contains genes for mating pheromone and pheromone receptor. Allelic variations in both subloci generate multiple B mating-types through which L. edodes maintains genetic diversity. In addition to the B mating-type locus, our genomic sequence analysis revealed the presence of a novel chromosomal locus 43.3 kb away from the B mating-type locus, containing genes for a pair of mating pheromones (PHBN1 and PHBN2) and a pheromone receptor (RCBN). The new locus (Bα-N) was homologous to the Bα sublocus, but unlike the multiallelic Bα sublocus, it was highly conserved across the wild and cultivated strains. The interactions of RcbN with various mating pheromones from the B and Bα-N mating-type loci were investigated using yeast model that replaced endogenous yeast mating pheromone receptor STE2 with RCBN. The yeast mating signal transduction pathway was only activated in the presence of PHBN1 or PHBN2 in the RcbN producing yeast, indicating that RcbN interacts with self-pheromones (PHBN1 and PHBN2), not with pheromones from the B mating-type locus. The biological function of the Bα-N locus was suggested to control the expression of A mating-type genes, as evidenced by the increased expression of two A-genes HD1 and HD2 upon the treatment of synthetic PHBN1 and PHBN2 peptides to the monokaryotic strain of L. edodes.