• Korean Journal of Pharmacognosy
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• v.52 no.3
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• pp.192-201
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• 2021

Dangguisu-san (DGSS) is widely known traditional herbal medicinal formula in Korea for treatment of traumatic injury by traffic accident, ecchymosis, abdominal distension and anti-thrombosis of blood. This study was conducted to develop the simultaneous analyze method using high performance liquid chromatography (HPLC) and examine the effect of anti-inflammatory activity of DGSS-dry extract (DGSS-DE) and DGSS-mix extract powder (DGSS-MEP). Physicochemical characteristics of DGSS-DE and DGSS-MEP showed that there is no significant difference in pH, titratable acidity, total soluble solid content and browning degree except for color value (L, a, b). 15 functional constituents of DGSS were identified and the correlation coefficient values of DGSS-DE and DGSS-MEP were conformed 0.950. Also, DGSS-DE and DGSS-MEP significantly decreased the secretion of nitric oxide (NO), prostaglandin E₂ (PGE₂), interleukin-1β (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) through inhibited expression of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), IL-1β, IL-6, and TNF-α. From these result, DGSS-MEP showed similar chemical composition and anti-inflammatory effect to DGSS-DE. Therefore, DGSS-DE and DGSS-MEP may be useful as potential source of drug to prevent inflammation.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.327-335
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• 2021

We aimed to find new space types and characteristics for creating gardens in the city through the type of idle space in the city, present guidelines that can be used in creating gardens in the future, and establish basic data for expanding green infrastructure. As a result, we found that the idle space in the city was classified into four types, and it was determined that differentiation should be given to the creation of each type. The achievements of this study can be a potential source of urban ecosystem services that can provide community benefits and opportunities for urban regeneration through the redevelopment of the community and support the health and well-being of local residents. In addition, urban idle space can be a valuable resource as a green infrastructure that can be used to support the health of urban ecosystems and improve the quality of life of urban residents.

• Journal of Microbiology and Biotechnology
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• v.30 no.12
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• pp.1927-1936
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• 2020

Tunicates are known to contain biologically active materials and one species in particular, the sea peach (Halocynthia aurantium), has not been thoroughly studied. In this study we aimed to analyze the fatty acids profile of the H. aurantium body wall and its immunomodulatory effects on RAW264.7 macrophage-like cells. The fatty acids were classified into three categories: saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and polyunsaturated fatty acids (PUFAs). Omega-3 fatty acid content, including EPA and DHA, was higher than omega-6 fatty acids. H. aurantium body wall fatty acids exhibited enhanced immune response and anti-inflammatory effects on RAW264.7 macrophage-like cells. Under normal conditions, fatty acids significantly increase nitric oxide (NO) and PGE2 production in a dose-dependent manner, thereby improving the immune response. On the other hand, in LPS-treated RAW264.7 cells, fatty acids significantly decreased nitric oxide (NO) and PGE2 production in a dose-dependent manner, thereby enhancing anti-inflammatory effects. Fatty acids transcriptionally control the expression of the immune-associated genes, iNOS, IL-1β, IL-6, COX-2, and TNF-α, via the MAPK and NF-κB signaling cascades in RAW264.7 cells. However, in LPS-stimulated RAW264.7 cells, H. aurantium body wall fatty acids significantly inhibited expression of inflammatory cytokine; similarly, production of COX-2 and PGE2 was inhibited. The results of our present study provide insight into the immune-improving and anti-inflammatory effects of H. aurantium body wall fatty acids on macrophages. In addition, our study demonstrates that H. aurantium body wall is a potential source of immune regulatory components.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4290-4309
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• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

• English & American cultural studies
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• v.14 no.2
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• pp.207-232
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• 2014

Scholars have considered Chaucer's House of Fame mostly as an ars poetica, in which the poet explores new poetic principles and subject matters, while making few attempts to understand the poem in its historical and social contexts. Investigating the nature of the "tidings" that Chaucer suggests as the new source of his poetic inspiration, this paper argues that the house of Rumor was modeled after late fourteenth century English society that experienced increased appetite for news. The political upheaval during the period from the English Rising in 1381 to the reign of Henry IV in the early fifteenth century produced an unprecedented amount of written and oral propaganda. The proliferation of seditious rumors as well as protests and promulgations during this period indicates how seriously medieval society was engaged with the circulation of news. Particularly, the case of John Shirle in 1381 and the legend about the survival of Richard II demonstrate the subversive power of medieval rumor that often served as a political discourse with which people expressed their oppositions to government. Conspicuous in the activities of both the government and late medieval political protestors was the extensive use of writing. The posting of bills in public places continued until the fifteenth century, when such activities became so common and dangerous that the government had to issue proclamations forbidding the circulation of such seditious writings. The number of extant royal proclamations, written protests, and pamphlets demonstrates that already in the late fourteenth and fifteenth centuries the notion of a discursive public space began to emerge. Whether written or orally transmitted, news and rumor circulated in late medieval England, creating a social space in which people shared their political opinions before the introduction of the early modern print culture. In The House of Fame Chaucer calls attention to the subversiveness of rumor, its potential as a public discourse, and the power of written communication in creating truth in order to appropriate these characteristics for his English poems.

• Biomaterials Research
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• v.22 no.4
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• pp.271-278
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• 2018

Background: The chondrogenic differentiation of mesenchymal stem cells (MSCs) is regulated by many factors, including oxygen tensions, growth factors, and cytokines. Evidences have suggested that low oxygen tension seems to be an important regulatory factor in the proliferation and chondrogenic differentiation in various MSCs. Recent studies report that synovium-derived mesenchymal stem cells (SDSCs) are a potential source of stem cells for the repair of articular cartilage defects. But, the effect of low oxygen tension on the proliferation and chondrogenic differentiation in SDSCs has not characterized. In this study, we investigated the effects of hypoxia on proliferation and chondrogenesis in SDSCs. Method: SDSCs were isolated from patients with osteoarthritis at total knee replacement. To determine the effect of oxygen tension on proliferation and colony-forming characteristics of SDSCs, A colony-forming unit (CFU) assay and cell counting-based proliferation assay were performed under normoxic (21% oxygen) or hypoxic (5% oxygen). For in vitro chondrogenic differentiation, SDSCs were concentrated to form pellets and subjected to conditions appropriate for chondrogenic differentiation under normoxia and hypoxia, followed by the analysis for the expression of genes and proteins of chondrogenesis. qRT-PCR, histological assay, and glycosoaminoglycan assays were determined to assess chondrogenesis. Results: Low oxygen condition significantly increased proliferation and colony-forming characteristics of SDSCs compared to that of SDSCs under normoxic culture. Similar pellet size and weight were found for chondrogensis period under hypoxia and normoxia condition. The mRNA expression of types II collagen, aggrecan, and the transcription factor SOX9 was increased under hypoxia condition. Histological sections stained with Safranin-O demonstrated that hypoxic conditions had increased proteoglycan synthesis. Immunohistochemistry for types II collagen demonstrated that hypoxic culture of SDSCs increased type II collagen expression. In addition, GAG deposition was significantly higher in hypoxia compared with normoxia at 21 days of differentiation. Conclusion: These findings show that hypoxia condition has an important role in regulating the synthesis ECM matrix by SDSCs as they undergo chondrogenesis. This has important implications for cartilage tissue engineering applications of SDSCs.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.79-85
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• 2021

After COVID-19, the number of individuals participating in delivery platforms has increased. They are using the participation of the delivery platform as a means of creating a new source of income as well as a means of sports and hobbies. This phenomenon is related to a social phenomenon called 'N-jober'. However, there are still few studies examining this phenomenon. Therefore, this study intends to examine the phenomenon of individual participation in delivery platforms and their issues. Text mining was performed on news data from January 2019, when COVID-19 started. As a result, social issues related to the increase in individual participation in delivery platforms were derived into 5 topics(Introduction to the Phenomenon, Characteristics of Participants, Participant's Income and Fees, Characteristics as a Job, Concern about Potential Risks). This study has significance in that it expanded the perspective of academic discussion on delivery platform business to individual participants.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.107-115
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• 2021

Purpose: This study aimed to demonstrate the presence of dental caries through a photoacoustic imaging system with visible and near-infrared wavelengths, highlighting the differences between the 2 spectral regions. The depth at which carious tissue could be detected was also verified. Materials and Methods: Fifteen permanent molars were selected and classified as being sound or having incipient or advanced caries by visual inspection, radiography, and optical coherence tomography analysis prior to photoacoustic scanning. A photoacoustic imaging system operating with a nanosecond pulsed laser as the light excitation source at either 532 nm or 1064 nm and an acoustic transducer at 5 MHz was developed, characterized, and used. En-face and lateral(depth) photoacoustic signals were detected. Results: The results confirmed the potential of the photoacoustic method to detect caries. At both wavelengths, photoacoustic imaging effectively detected incipient and advanced caries. The reconstructed photoacoustic images confirmed that a higher intensity of the photoacoustic signal could be observed in regions with lesions, while sound surfaces showed much less photoacoustic signal. Photoacoustic signals at depths up to 4 mm at both 532 nm and 1064 nm were measured. Conclusion: The results presented here are promising and corroborate that photoacoustic imaging can be applied as a diagnostic tool in caries research. New studies should focus on developing a clinical model of photoacoustic imaging applications in dentistry, including soft tissues. The use of inexpensive light-emitting diodes together with a miniaturized detector will make photoacoustic imaging systems more flexible, user-friendly, and technologically viable.

• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.260-267
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• 2021

In this study, a carboxylate-based anionic surfactant SLEC-3 was prepared from coconut oil and the structure was elucidated by using FT-IR, ¹H-NMR and ¹³C-NMR analysis. Measurements of interfacial properties such as critical micelle concentration, static and dynamic surface tensions, emulsification index, and foam stability have shown that SLEC-3 is better in terms of interfacial activity and more effective in lowering interfacial free energy than those of SLES, which has been widely used as a conventional anionic surfactant in the detergent industry. Biodegradability, acute oral toxicity and dermal irritation tests also revealed that SLEC-3 surfactant possesses excellent mildness and low toxicity, indicating the potential applicability in detergents and cleaner products formulation.