• Title/Summary/Keyword: Data Clustering

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Experimental Studies on the Skin Barrier Improvement and Anti-inflammatory Activity based on a Bibliometric Network Map

  • Eunsoo Sohn;Sung Hyeok Kim;Chang Woo Ha;Sohee Jang;Jung Hun Choi;Hyo Yeon Son;Cheol-Joo Chae;Hyun Jung Koo;Eun-Hwa Sohn
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2023.04a
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    • pp.40-40
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    • 2023
  • Atopic dermatitis is a chronic inflammatory skin diseases caused by skin barrier dysfunction. Allium victoralis var. Platyphyllum (AVP) is a perennial plant used as vegetable and herbal medicine. The purpose of this study was to suggest that AVP is a new cosmetic material by examining the effects of AVP on the skin barrier and inflammatory response. A bibliometric network analysis was performed through keyword co-occurrence analysis by extracting author keyword from 69 articles retrieved from SCOPUS. We noted the anti-inflammatory activity shown by the results of clustering and mapping from network visualization analysis using VOSviewer software tool. HPLC-UV analysis showed that AVP contains 0.12 ± 0.02 mg/g of chlorogenic acid and 0.10 ± 0.01 mg/g of gallic acid. AVP at 100 ㎍/mL was shown to increase the mRNA levels of filaggrin and involucrin related to skin barrier function by 1.50-fold and 1.43-fold, respectively. In the scratch assay, AVP at concentrations of 100 ㎍/mL and 200 ㎍/mL significantly increased the cell migration rate and narrowed the scratch area. In addition, AVP suppressed the increase of inflammation-related factors COX-2 and NO and decreased the release of β-hexosaminidase. This study suggests that AVP can be developed as a functional cosmetic material for atopy management through skin barrier protection effects, anti-inflammatory and anti-itch effects.

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An Observational Multi-Center Study Protocol for Distribution of Pattern Identification and Clinical Index in Parkinson's Disease (파킨슨병 변증 유형 및 지표 분포에 대한 전향적 다기관 관찰연구 프로토콜)

  • HuiYan Zhao;Ojin Kwon;Bok-Nam Seo;Seong-Uk Park;Horyong Yoo;Jung-Hee Jang
    • The Journal of Internal Korean Medicine
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    • v.45 no.1
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    • pp.1-10
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    • 2024
  • Objectives: This study investigated the pattern identification (PI) and clinical index of Parkinson's disease (PD) for personalized diagnosis and treatment. Methods: This prospective observational multi-center study recruited 100 patients diagnosed with PD from two Korean medicine hospitals. To cluster new subtypes of PD, items on a PI questionnaire (heat and cold, deficiency and excess, visceral PI) were evaluated along with pulse and tongue analysis. Gait analysis was performed and blood and feces molecular signature changes were assessed to explore biomarkers for new subtypes. In addition, unified PD rating scale II and III scores and the European quality of life 5-dimension questionnaire were assessed. Results: The clinical index obtained in this study analyzed the frequency statistics and hierarchical clustering analysis to classify new subtypes based on PI. Moreover, the biomarkers and current status of herbal medicine treatment were analyzed using the new subtypes. The results provide comprehensive data to investigate new subtypes and subtype-based biomarkers for the personalized diagnosis and treatment of PD patients. Ethical approval was obtained from the medical ethics committees of the two Korean medicine hospitals. All amendments to the research protocol were submitted and approved. Conclusions: An objective and standardized diagnostic tool is needed for the personalized treatment of PD by traditional Korean medicine. Therefore, we developed a clinical index as the basis for the PI clinical evaluation of PD. Trial Registration: This trial is registered with the Clinical Research Information Service (CRIS) (KCT0008677)

Transcriptome Analysis of the Striatum of Electroacupuncture-treated Naïve and Ischemic Stroke Mice

  • Hong Ju Lee;Hwa Kyoung Shin;Ji-Hwan Kim;Byung Tae Choi
    • Journal of Pharmacopuncture
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    • v.27 no.2
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    • pp.162-171
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    • 2024
  • Objectives: Electroacupuncture (EA) has been demonstrated to aid stroke recovery. However, few investigations have focused on identifying the potent molecular targets of EA by comparing EA stimulation between naïve and disease models. Therefore, this study was undertaken to identify the potent molecular therapeutic mechanisms underlying EA stimulation in ischemic stroke through a comparison of mRNA sequencing data obtained from EA-treated naïve control and ischemic stroke mouse models. Methods: Using both naïve control and middle cerebral artery occlusion (MCAO) mouse models, EA stimulation was administered at two acupoints, Baihui (GV20) and Dazhui (GV14), at a frequency of 2 Hz. Comprehensive assessments were conducted, including behavioral evaluations, RNA sequencing to identify differentially expressed genes (DEGs), functional enrichment analysis, protein-protein interaction (PPI) network analysis, and quantitative real-time PCR. Results: EA stimulation ameliorated the ischemic insult-induced motor dysfunction in mice with ischemic stroke. Comparative analysis between control vs. MCAO, control vs. control + EA, and MCAO vs. MCAO + EA revealed 4,407, 101, and 82 DEGs, respectively. Of these, 30, 7, and 1 were common across the respective groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed upregulated DEGs associated with the regulation of inflammatory immune response in the MCAO vs. MCAO + EA comparison. Conversely, downregulated DEGs in the control vs. control + EA comparison were linked to neuronal development. PPI analysis revealed major clustering related to the regulation of cytokines, such as Cxcl9, Pcp2, Ccl11, and Cxcl13, in the common DEGs of MCAO vs. MCAO + EA, with Esp8l1 identified as the only common downregulated DEG in both EA-treated naïve and ischemic models. Conclusion: These findings underscore the diverse potent mechanisms of EA stimulation between naïve and ischemic stroke mice, albeit with few overlaps. However, the potent mechanisms underlying EA treatment in ischemic stroke models were associated with the regulation of inflammatory processes involving cytokines.

Assessment of Antarctic Ice Tongue Areas Using Sentinel-1 SAR on Google Earth Engine (Google Earth Engine의 Sentienl-1 SAR를 활용한 남극 빙설 면적 변화 모니터링)

  • Na-Mi Lee;Seung Hee Kim;Hyun-Cheol Kim
    • Korean Journal of Remote Sensing
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    • v.40 no.3
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    • pp.285-293
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    • 2024
  • This study explores the use of Sentinel-1 Synthetic Aperture Radar (SAR), processed through Google Earth Engine (GEE), to monitor changes in the areas of Antarctic ice shelves. Focusing on the Campbell Glacier Tongue (CGT) and Drygalski Ice Tongue (DIT),the research utilizes GEE's cloud computing capabilities to handle and analyze large datasets. The study employs Otsu's method for image binarization to distinguish ice shelves from the ocean and mitigates detection errors by averaging monthly images and extracting main regions. Results indicate that the CGT area decreased by approximately 26% from January 2016 to January 2024, primarily due to calving events,while DIT showed a slight increase overall,with notable reduction in recent years. Validation against Sentinel-2 optical images demonstrates high accuracy,underscoring the effectiveness of SAR and GEE for continuous, long-term monitoring of Antarctic ice shelves.

Arabic Stock News Sentiments Using the Bidirectional Encoder Representations from Transformers Model

  • Eman Alasmari;Mohamed Hamdy;Khaled H. Alyoubi;Fahd Saleh Alotaibi
    • International Journal of Computer Science & Network Security
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    • v.24 no.2
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    • pp.113-123
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    • 2024
  • Stock market news sentiment analysis (SA) aims to identify the attitudes of the news of the stock on the official platforms toward companies' stocks. It supports making the right decision in investing or analysts' evaluation. However, the research on Arabic SA is limited compared to that on English SA due to the complexity and limited corpora of the Arabic language. This paper develops a model of sentiment classification to predict the polarity of Arabic stock news in microblogs. Also, it aims to extract the reasons which lead to polarity categorization as the main economic causes or aspects based on semantic unity. Therefore, this paper presents an Arabic SA approach based on the logistic regression model and the Bidirectional Encoder Representations from Transformers (BERT) model. The proposed model is used to classify articles as positive, negative, or neutral. It was trained on the basis of data collected from an official Saudi stock market article platform that was later preprocessed and labeled. Moreover, the economic reasons for the articles based on semantic unit, divided into seven economic aspects to highlight the polarity of the articles, were investigated. The supervised BERT model obtained 88% article classification accuracy based on SA, and the unsupervised mean Word2Vec encoder obtained 80% economic-aspect clustering accuracy. Predicting polarity classification on the Arabic stock market news and their economic reasons would provide valuable benefits to the stock SA field.

Analysis of Determinants of Civilian City Gas Demand Considering Spatial Correlation (공간적 상관성을 고려한 민수용 도시가스 수요결정 요인 분석)

  • Eunbi Park;DooHwan Won
    • Environmental and Resource Economics Review
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    • v.33 no.1
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    • pp.59-86
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    • 2024
  • Recently, research on city gas demand is increasing by reflecting the characteristics of each region. The similarity of the social structure of the adjacent region and the density of the supply infrastructure induce spatial correlation with the clustering that has a microscopic relationship between regions. Accordingly, as a result of analyzing the spatial correlation after dividing the demand for city gas for civilian use into a total of 54 regions based on the jurisdiction of 34 city gas companies, it was confirmed that there was a positive spatial correlation from a global and local perspective. In this study, the demand for city gas for civilian use for 54 regions from January 2014 to December 2022 was composed of panel data, and the spatial panel regression analysis and the general panel regression analysis were compared, and it was found that the spatial error model (SEM) was the most suitable model. This presents policy and practical implications by confirming that the demand for city gas for civilian use in one region has a significant relationship with the adjacent region.

Bacterial communities in the feces of insectivorous bats in South Korea

  • Injung An;Byeori Kim;Sungbae Joo;Kihyun Kim;Taek-Woo Lee
    • Journal of Ecology and Environment
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    • v.48 no.2
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    • pp.120-127
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    • 2024
  • Bats serve as vectors and natural reservoir hosts for various infectious viruses, bacteria, and fungi. These pathogens have also been detected in bat feces and can cause severe illnesses in hosts, other animals, and humans. Because pathogens can easily spread into the environment through bat feces, determining the bacterial communities in bat guano is crucial to mitigate potential disease transmission and outbreaks. This study primarily aimed to examine bacterial communities in the feces of insectivorous bats living in South Korea. Fecal samples were collected after capturing 84 individuals of four different bat species in two regions of South Korea, and the bacterial microbiota was assessed through next generation sequencing of the 16S rRNA gene. The results revealed that, with respect to the relative abundance at the phylum level, Myotis bombinus was dominated by Firmicutes (47.24%) and Proteobacteria (42.66%) whereas Miniopterus fuliginosus (82.78%), Rhinolophus ferrumequinum (63.46%), and Myotis macrodactylus (78.04%) were dominated by Proteobacteria. Alpha diversity analysis showed no difference in abundance between species and a significant difference (p < 0.05) between M. bombinus and M. fuliginosus. Beta-diversity analysis revealed that Clostridium, Asaia, and Enterobacteriaceae_g were clustered as major factors at the genus level using principal component analysis. Additionally, linear discriminant analysis effect size was conducted based on relative expression information to select bacterial markers for each bat species. Clostridium was relatively abundant in M. bombinus, whereas Mycoplasma_g10 was relatively abundant in R. ferrumequinum. Our results provide an overview of bat guano microbiota diversity and the significance of pathogenic taxa for humans and the environment, highlighting a better understanding of preventing emerging diseases. We anticipate that this research will yield bioinformatic data to advance our knowledge of overall microbial genetic diversity and clustering characteristics in insectivorous bat feces in South Korea.

The Study of Land Surface Change Detection Using Long-Term SPOT/VEGETATION (장기간 SPOT/VEGETATION 정규화 식생지수를 이용한 지면 변화 탐지 개선에 관한 연구)

  • Yeom, Jong-Min;Han, Kyung-Soo;Kim, In-Hwan
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.4
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    • pp.111-124
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    • 2010
  • To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.

Comparison of Algorithms for Generating Parametric Image of Cerebral Blood Flow Using ${H_2}^{15}O$ PET Positron Emission Tomography (${H_2}^{15}O$ PET을 이용한 뇌혈류 파라메트릭 영상 구성을 위한 알고리즘 비교)

  • Lee, Jae-Sung;Lee, Dong-Soo;Park, Kwang-Suk;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
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    • v.37 no.5
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    • pp.288-300
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    • 2003
  • Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

The Risk Assessment of the Fire Occurrence According to Urban Facilities in Jinju-si (진주시 도시시설물별 화재발생 위험도 평가)

  • Bae, Gyu Han;Won, Tae Hong;Yoo, Hwan Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.24 no.1
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    • pp.43-50
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    • 2016
  • Urbanization in Korea has increased significantly and subsequently, various facilities have been concentrated in urban areas at high speed in accordance with a growing urban population. Accordingly, damages have occurred due to a variety of disasters. In particular, fire damage among the social disasters caused the most severe damage in urban areas along with traffic accidents. 44,432 cases of fire occurred in 2015 in Korea. Due to these accidents, 253 were killed and property damage of 4,50 billion won was generated. However, despite the efforts to reduce a variety of damage, fire danger still remains high. In this regard, this study collected fire data, generated from 2007 to 2014 through the Jinju Fire Department and the National Fire Data System(NFDS) and calculated fire risk by analyzing the clustering of fire cases and facilities in Jinju-si based on the current DB of facilities, offered by the Ministry of Government Administration and Home Affairs. As a result, the risk ratings of fire occurrence were classified as four stages under the standards of the US Society of Fire Protection Engineers(SEPE). Business facilities, entertainment facilities, and automobile facilities were classified as the highest A grade, detached houses, Apartment houses, education facilities, sales facilities, accommodation, set of facilities, medical facilities, industrial facilities, and life service facilities were classified as U grade, and other facilities were classified as EU grade. Finally, hazardous production facilities were classified as BEU grade, the lowest grade. In addition, in the case of setting the standard with loss of life, the highest risk facility was the hazardous production facilities, while in the case of setting the standard with property damage, a set of facilities and industrial facilities showed the highest risk. In this regard, this study is expected to be effectively utilized to establish the fire reduction measures against facilities, distributed in urban space by calculating risk grades regarding the generation frequency, casualties, and property damage, through the classification of fire, occurred in the city, according to the facilities.