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Whole-genome resequencing reveals domestication and signatures of selection in Ujimqin, Sunit, and Wu Ranke Mongolian sheep breeds

  • Wang, Hanning;Zhong, Liang;Dong, Yanbing;Meng, Lingbo;Ji, Cheng;Luo, Hui;Fu, Mengrong;Qi, Zhi;Mi, Lan
    • Animal Bioscience
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    • v.35 no.9
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    • pp.1303-1313
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    • 2022
  • Objective: The current study aimed to perform whole-genome resequencing of Chinese indigenous Mongolian sheep breeds including Ujimqin, Sunit, and Wu Ranke sheep breeds (UJMQ, SNT, WRK) and deeply analyze genetic variation, population structure, domestication, and selection for domestication traits among these Mongolian sheep breeds. Methods: Blood samples were collected from a total of 60 individuals comprising 20 WRK, 20 UJMQ, and 20 SNT. For genome sequencing, about 1.5 ㎍ of genomic DNA was used for library construction with an insert size of about 350 bp. Pair-end sequencing were performed on Illumina NovaSeq platform, with the read length of 150 bp at each end. We then investigated the domestication and signatures of selection in these sheep breeds. Results: According to the population and demographic analyses, WRK and SNT populations were very similar, which were different from UJMQ populations. Genome wide association study identified 468 and 779 significant loci from SNT vs UJMQ, and UJMQ vs WRK, respectively. However, only 3 loci were identified from SNT vs WRK. Genomic comparison and selective sweep analysis among these sheep breeds suggested that genes associated with regulation of secretion, metabolic pathways including estrogen metabolism and amino acid metabolism, and neuron development have undergone strong selection during domestication. Conclusion: Our findings will facilitate the understanding of Chinese indigenous Mongolian sheep breeds domestication and selection for complex traits and provide a valuable genomic resource for future studies of sheep and other domestic animal breeding.

Audiobook Text Shaping for Synesthesia Voice Training - Focusing on Paralanguages - (오디오북 텍스트 형상화를 위한 공감각적 음성 훈련 연구 - 유사언어를 활용하여 -)

  • Cho, Ye-Shin;Choi, Jae-Oh
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.8
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    • pp.167-180
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    • 2019
  • The purpose of this study is to find out the results of synesthesia speech training using similar language for shaping audiobook text. The audiobook text for training uses Tolstoy's work, and uses similar language of tone, tone, pose, speed, intonation, accent, and expression of emotions. The participants who ten visually impaired trainee in H library were selected for qualitative research. Based on the research questions raised in this study, the results are as follows. First, synesthesia training, in which more than two senses of the five senses work simultaneously in voice training for audio book text shaping, produced the result by visualizing the original purpose, meaning, and background of the text. Second, the use of similar language was helpful in the whole process of expressing the meaning of sentence and dialogue for audiobook text shaping. In addition, although there were some differences among the study subjects, they found commonalities that considered tone, pose, and intonation important. Third, the visually impaired have advanced sensory aspects and memory, which resulted in rapid acquisition of metabolism and acceptance of transmission during training. In addition, the teacher's friendly behavior was a very important key mediator in the training process.

SNS Effect of the negative event on the Firm Performance: Comparison between Pre and Post SNS media appearance

  • Kim, Sang Yong;Lee, Da Eun
    • Asia Marketing Journal
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    • v.16 no.1
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    • pp.21-33
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    • 2014
  • When the negative event is published, the company tends to go through the negative impact on the firm performance. Especially, with the SNS, the negative event is instantly spread on indefinite region so the impact seems bigger than the period before the SNS media appearance. It seems that everyone considers the SNS media impact on the firm performance quite big. However, there has been no empirical study on the impact comparison on the firm performance between pre and post SNS media occurrence periods. This study tries to empirically compare the impact of the negative event on the firm performance between pre and post SNS media appearance. Our study starts fromthe basic but not verified question; Does really the negative event have more negative impact in the post-SNS-occurrence period than in the pre-SNS-occurrence period? In order to examine the impact of the negative publicity on firm performance in two eras, pre and post SNS media appearance, we used CAR (Cumulative Abnormal Resturns) model. By using this model, we could verify the statistical significance of cumulative abnormal returns in market between before and after the events. For event samples, we focused on food manufacturers and collected the negative events from 1991 to 2003 for pre-SNS occurrence period, and from 2010 to 2013 for post-SNS occurrence period. Based on the listed food companies at KOSPI, we researched Naver News Library (newslibrary.naver.com) and Naver News (news.naver.com) for all the individual negative events published for both periods. Firm returns data were collected from TS 2000 (KOCO Info) and market portfolio data were collected from KRX Exchange. Through our empirical analysis, our finding is interesting to note that the type of events differently influences on the firm performance. With the SNS, the health-related events have influence on the firm performance 'after the event day' whereas the company behavior trust events have influence 'before the event day'. Our findings have implications for management. When a negative event directly related to or threatening customers or their life such as health, it is crucial to fix up the situation right after the event occurs. On the other hand, when a negative event is not publicly available information such as company behavior trust, it is important for marketers to strengthen the firms' trust reputation and control the bad WOM before the event.

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Influence of the root canal filling technique on the success rate of primary endodontic treatments: a systematic review

  • Daniel Feijolo Marconi ;Giovana Siocheta da Silva ;Theodoro Weissheimer;Isadora Ames Silva ;Gabriel Barcelos So;Leonardo Thomasi Jahnke ;Jovito Adiel Skupien ; Marcus Vinicius Reis So ; Ricardo Abreu da Rosa
    • Restorative Dentistry and Endodontics
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    • v.47 no.4
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    • pp.40.1-40.18
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    • 2022
  • Objectives: This study aimed to investigate the influence of different obturation techniques compared to cold lateral compaction on the success rate of primary non-surgical endodontic treatments. Materials and Methods: Systematic searches were performed for studies published up to May 17th, 2022 in MEDLINE/PubMed, Cochrane Library, Web of Science, Scopus, EMBASE, and Grey Literature Reports. Randomized clinical trials and nonrandomized (nonrandomized clinical trials, prospective or retrospective) studies that evaluated the success rate of primary non-surgical endodontic treatments obturated with the cold lateral compaction (control) and other obturation techniques were included. The revised Cochrane risk of bias tools for randomized trials (RoB 2) and nonrandomized studies of interventions (ROBINS-I) were used to evaluate the risk of bias. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool was used to evaluate the certainty of evidence. Results: Eleven studies (4 randomized clinical trials (RCTs), 4 prospective, and 3 retrospectives) were included. Two RCTs were classified as having some concerns risk of bias and 2 as a low risk of bias. Two nonrandomized studies were classified as having a critical risk of bias and 5 as having a moderate risk of bias. The GRADE analysis demonstrated a very low to moderate certainty of evidence. Conclusions: This systematic review generally evidenced no differences in the success rate of primary non-surgical endodontic treatments when the cold lateral compaction technique and other obturation techniques are performed. Further well-designed studies are still necessary.

Herbal Medicine for Premenstrual Syndrome: A Systematic Review and Meta-analysis (월경전증후군에 대한 한약 치료의 효과 : 체계적 문헌 고찰과 메타 분석)

  • Ji-In Seo;Yun-Jae Lee;Seo-Lim Ko;Nu-Ree Kim;Jeong-Hun Kim;Mi-Ju Son;Young-Eun Kim;An-Na Kim;Eun-Hee Lee
    • The Journal of Korean Obstetrics and Gynecology
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    • v.36 no.4
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    • pp.96-120
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    • 2023
  • Objectives: This study reports the findings that support the efficacy of herbal medicine (HM) for premenstrual syndrome (PMS). Methods: We conducted meta-analysis of findings from randomized controlled trials (RCTs) for PMS treated with HM. The articles were published before July 2022, located using 9 databases (Pubmed, EMBASE, Cochrane Library, CINAHL, CNKI, CiNii, SCIENCE ON, KoreaMed, OASIS). Results: We observed 2,034 studies, of which 23 RCTs met our inclusion criteria. The risk of bias in the included studies was relatively unclear or high. Meta-analysis of 3 RCTs showed that HM group had a significantly higher total effective rate than the western medicine group (RR 1.20 [95% CI 1.06, 1.36, p=0.004]). Meta-analysis of 1 RCT showed that HM group had a significantly lower symptom score (MD -3.04 [95% CI -5.36, -0.72, p=0.01]), while there was no significant difference in daily record of severity of problems scale (MD -20.52 [95% CI -49.33, 8.29, p=0.16]). Conclusions: HM significantly improved PMS symptoms than general treatment and no serious adverse events were reported. However, the evidence on the effectiveness and safety of HM for PMS was not enough to provide reliable results due to the small number and low quality of included studies. We believe that rigorous RCTs will lead to more reliable evidence of the intervention.

Introduction of a New Method for Total Organic Carbon and Total Nitrogen Stable Isotope Analysis of Dissolved Organic Matter in Aquatic Environments (수환경 내 용존성 유기물질의 총 유기탄소 및 총 질소 안정동위원소 신규 분석법 소개)

  • Si-yeong Park;Heeju Choi;Seoyeon Hong;Bo Ra Lim;Seoyeong Choi;Eun-Mi Kim;Yujeong Huh;Soohyung Lee;Min-Seob Kim
    • Korean Journal of Ecology and Environment
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    • v.56 no.4
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    • pp.339-347
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    • 2023
  • Dissolved organic matter (DOM) is a key component in the biogeochemical cycling in freshwater ecosystem. However, it has been rarely explored, particularly complex river watershed dominated by natural and anthropogenic sources, such as various effluent facility and livestock. The current research developed a new analytical method for TOC/TN (Total Organic Carbon/Total Nitrogen) stable isotope ratio, and distinguish DOM source using stable isotope value (δ13C-DOC) and spectroscopic indices (fluorescence index [FI] and biological index [BIX]). The TOC/TN-IR/MS analytical system was optimized and precision and accuracy were secured using two international standards (IAEA-600 Caffein, IAEA-CH-6 Sucrose). As a result of controlling the instrumental conditions to enable TOC stable isotope analysis even in low-concentration environmental samples (<1 mgC L-1), the minimum detection limit was improved. The 12 potential DOM source were collected from watershed, which includes top-soils, groundwater, plant group (fallen leaves, riparian plants, suspended algae) and effluent group (pig and cow livestock, agricultural land, urban, industry facility, swine facility and wastewater treatment facilities). As a result of comparing characteristics between 12 sources using spectroscopic indices and δ13C-DOC values, it were divided into four groups according to their characteristics as a respective DOM sources. The current study established the TOC/TN stable isotope analyses system for the first time in Korea, and found that spectroscopic indices and δ13C-DOC are very useful tool to trace the origin of organic matter in the aquatic environments through library database.

Application of peak based-Bayesian statistical method for isotope identification and categorization of depleted, natural and low enriched uranium measured by LaBr3:Ce scintillation detector

  • Haluk Yucel;Selin Saatci Tuzuner;Charles Massey
    • Nuclear Engineering and Technology
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    • v.55 no.10
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    • pp.3913-3923
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    • 2023
  • Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(241Am, 57Co, 137Cs, 54Mn, 60Co), and then applied to five standard nuclear materials(0.32-4.51% at.235U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for 238U and 4.7-10.5% for 235U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify 235U and 238U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.

Analyzing the Main Paths and Intellectual Structure of the Data Literacy Research Domain (데이터 리터러시 연구 분야의 주경로와 지적구조 분석)

  • Jae Yun Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.403-428
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    • 2023
  • This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

An Exploratory Study of Generative AI Service Quality using LDA Topic Modeling and Comparison with Existing Dimensions (LDA토픽 모델링을 활용한 생성형 AI 챗봇의 탐색적 연구 : 기존 AI 챗봇 서비스 품질 요인과의 비교)

  • YaeEun Ahn;Jungsuk Oh
    • Journal of Service Research and Studies
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    • v.13 no.4
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    • pp.191-205
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    • 2023
  • Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.

Quantitative Analysis of X-Ray Fluorescence for Understanding the Effect of Elevated Temperatures on Cement Pastes (XRF (X-ray fluorescence)를 활용한 고온환경에 노출된 시멘트 페이스트 분석의 이해)

  • Kil-Song Jeon;Young-Sun Heo
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.6
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    • pp.130-137
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    • 2023
  • By using XRF (X-ray fluorescence), this study investigates the variation of chemical properties in cement pastes at elevated temperatures. High-temperature conditions were prepared by using an electric furnace, planning a total of 11 target temperatures ranging from room temperature to 1000 ℃. A standard library of geo-quant basic was applied for the analysis of 12 elements in cement paste, including Ca, Si, Al, Fe, S, Mg, Ti, Sr, P, Mn, Zn and K. The results revealed that, as the temperature increased, the proportion of each element in the cement paste also increased. With the exception of a few elements present in extremely low amounts in the cement pastes, the variation in the composition ratio of most elements exhibited a strong correlation with temperature, with an R-squared value exceeding 0.98. In this study, cement pastes exposed to normal and high-temperature environments were compared. The authors established that the reasons for the different results in this comparison can be explained from the same perspective as when comparing raw cement with cement paste. Furthermore, this study discussed the potentially most dominant parameter when investigating the properties of cement paste using XRF.