• Asian-Australasian Journal of Animal Sciences
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• v.29 no.12
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• pp.1696-1701
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• 2016

Japanese quail is still used as a model for poultry research because of their usefulness as laying, meat, and laboratory animals. Microsatellite markers are the most widely used molecular markers, due to their relative ease of scoring and high levels of polymorphism. The objective of the research was to determine genetic diversity and population genetic structures of selected Japanese quail lines (high body weight 1 [HBW1], HBW2, low body weight [LBW], and layer [L]) throughout 15th generations and an unselected control (C). A total of 69 individuals from five quail lines were genotyped by fifteen microsatellite markers. When analyzed profiles of the markers the observed ($H_o$) and expected ($H_e$) heterozygosity ranged from 0.04 (GUJ0027) to 0.64 (GUJ0087) and 0.21 (GUJ0027) to 0.84 (GUJ0037), respectively. Also, $H_o$ and $H_e$ were separated from 0.30 (L and LBW) to 0.33 (C and HBW2) and from 0.52 (HBW2) to 0.58 (L and LBW), respectively. The mean polymorphic information content (PIC) ranged from 0.46 (HBW2) to 0.52 (L). Approximately half of the markers were informative ($PIC{\geq}0.50$). Genetic distances were calculated from 0.09 (HBW1 and HBW2) to 0.33 (C and L). Phylogenetic dendrogram showed that the quail lines were clearly defined by the microsatellite markers used here. Bayesian model-based clustering supported the results from the phylogenetic tree. These results reflect that the set of studied markers can be used effectively to capture the magnitude of genetic variability in selected Japanese quail lines. Also, to identify markers and alleles which are specific to the divergence lines, further generations of selection are required.

• The Korea Journal of Herbology
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• v.26 no.1
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• pp.119-124
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• 2011

Objective : This study was carried out to investigate effect of korean medicinal herbs-included hair tonic (MHT) and food (MF) on hair growth in an alopecia model of C57BL/6 mice. Methods : Six-weeks old mice were given laboratory rodent chow diet for 1 week. Then, we used a depilatory for hair removal on mice. The next day, mice were randomized and separated in 3 groups of 6 mice; normal group (N, vehicle epidermal application+normal diet-treated group), positive control group (C, 3% minoxidil sulfate epidermal application+normal diet-treated group), and the treatment group (T, HT epidermal application+ MF diet-treated group). The hair regrowth was determined by photograph, which was taken at 7, 14 and 21 days. And scoring indices, hair density and hair thickness, were evaluated by Folliscope at same day. In addition, the hair regrowth was analyzed insulin-like growth factor (IGF-1) in the dorsal skin of mice. Results : As a result, not only external appearance but also hair density and hair thickness on dorsal skin were increased more in C, T groups than in N group at 21 days with mixed treatment. Therefore, distinct regrowth pattern is appeared by treatment of herbal tonic and natural food for 21 days. Also, the expressions of IGF-1 on dorsal skin were higher in C, T groups than in N group. Conclusion : These results suggested that this herbal hair tonic and natural food has hair growth promoting activities and may be useful for treatment of bald or alopecia.

• Journal of Internet Computing and Services
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• v.14 no.3
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• pp.23-33
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• 2013

Recently in the field of IT, cloud computing technology has been deployed rapidly in the current society because of its flexibility, efficiency and cost savings features. However, cloud computing system has a big problem of vulnerability in security. In order to solve the vulnerability of cloud computing systems security in this study, impact types of virtual machine about the vulnerability were determined and the priorities were determined according to the risk evaluation of virtual machine's vulnerability. For analyzing the vulnerability, risk measurement standards about the vulnerability were defined based on CVSS2.0, which is an open frame work; and the risk measurement was systematized by scoring for relevant vulnerabilities. Vulnerability risk standards are considered to suggest fundamental characteristics of vulnerability and to provide the degree of risks and consequently to be applicable to technical guides to minimize the vulnerability. Additionally, suggested risk standard of vulnerability is meaningful as the study content itself and could be used in technology policy project which is to be conducted in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.1-10
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• 2018

Current evaluation practices for IT projects suffer from several problems, which include the difficulty of self-explanation for the evaluation results and the improperly scaled scoring system. This study aims to develop a methodology of opinion mining to extract key factors for the causal relationship analysis and to assess the feasibility of quantifying evaluation scores from text comments using opinion mining based on big data analysis. The research has been performed on the domain of publicly procured IT proposal evaluations, which are managed by the National Procurement Service. Around 10,000 sets of comments and evaluation scores have been gathered, most of which are in the form of digital data but some in paper documents. Thus, more refined form of text has been prepared using various tools. From them, keywords for factors and polarity indicators have been extracted, and experts on this domain have selected some of them as the key factors and indicators. Also, those keywords have been grouped into into dimensions. Causal relationship between keyword or dimension factors and evaluation scores were analyzed based on the two research models-a keyword-based model and a dimension-based model, using the correlation analysis and the regression analysis. The results show that keyword factors such as planning, strategy, technology and PM mostly affects the evaluation result and that the keywords are more appropriate forms of factors for causal relationship analysis than the dimensions. Also, it can be asserted from the analysis that evaluation scores can be composed or calculated from the unstructured text comments using opinion mining, when a comprehensive dictionary of polarity for Korean language can be provided. This study may contribute to the area of big data-based evaluation methodology and opinion mining for IT proposal evaluation, leading to a more reliable and effective IT proposal evaluation method.

• Annals of Laboratory Medicine
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• v.38 no.6
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• pp.495-502
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• 2018

Background: Molecular genetic abnormalities are observed in over 90% of chronic myelomonocytic leukemia (CMML) cases. Recently, several studies have demonstrated the negative prognostic impact of ASXL1 mutations in CMML patients. We evaluated the prognostic impact of ASXL1 mutations and compared five CMML prognostic models in Korean patients with CMML. Methods: We analyzed data from 36 of 57 patients diagnosed as having CMML from January 2000 to March 2016. ASXL1 mutation analysis was performed by direct sequencing, and the clinical and laboratory features of patients were compared according to ASXL1 mutation status. Results: ASXL1 mutations were detected in 18 patients (50%). There were no significant differences between the clinical and laboratory characteristics of ASXL1-mutated ($ASXL1^+$) CMML and ASXL1-nonmutated ($ASXL1^-$) CMML patients (all P >0.05). During the median follow-up of 14 months (range, 0-111 months), the overall survival (OS) of $ASXL1^+$ CMML patients was significantly inferior to that of $ASXL1^-$ CMML patients with a median survival of 11 months and 19 months, respectively (log-rank P =0.049). An evaluation of OS according to the prognostic models demonstrated inferior survival in patients with a higher risk category according to the Mayo molecular model (log-rank P =0.001); the other scoring systems did not demonstrate a significant association with survival. Conclusions: We demonstrated that ASXL1 mutations, occurring in half of the Korean CMML patients examined, were associated with inferior survival. ASXL1 mutation status needs to be determined for risk stratification in CMML.

• Journal of Veterinary Science
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• v.21 no.3
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• pp.21.1-21.14
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• 2020

Background: Physical exercise is known to cause significant joint changes. Thus, monitoring joint behavior of athletic horses is essential in early disorders recognition, allowing the proper management. Objectives: The aims of this study were to determine the morphological patterns, physical examination characteristics and ultrasound findings of show jumping horses in training and to establish a score-based examination model for physical and ultrasound follow-ups of metacarpophalangeal joint changes in these animals. Methods: A total of 52 metacarpophalangeal joints from 26 horses who were initially in the taming stage were evaluated, and the horses' athletic progression was monitored. The horses were evaluated by a physical examination and by B-mode and Doppler-mode ultrasound examinations, starting at time zero (T0), which occurred concomitantly with the beginning of training, and every 3 months thereafter for a follow-up period of 18 months. Results: The standardized examination model revealed an increase in the maximum joint flexion angles and higher scores on the physical and ultrasound examinations after scoring was performed by predefined assessment tools, especially between 3 and 6 months of evaluation, which was immediately after the horses started more intense training. The lameness score and the ultrasound examination score were slightly higher at the end of the study. Conclusions: The observed results were probably caused by the implementation of a training regimen and joint adaptation to physical conditioning. The joints most likely undergo a pre-osteoarthritic period due to work overload, which can manifest in a consistent or adaptive manner, as observed during this study. Thus, continuous monitoring of young athlete horses by physical and ultrasound examinations that can be scored is essential.

• Clinical and Experimental Reproductive Medicine
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• v.50 no.4
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• pp.292-298
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• 2023

Objective: Ovarian torsion is a gynecological disorder that causes ischemia-reperfusion injuries in the ovary. Our study investigated berberine's short- and long-term effects on ovarian ischemia-reperfusion injuries. Methods: This study included 28 Wistar albino female rats weighing 180 to 220 g, which were divided into four groups: sham (S), torsion/detorsion (T/D), torsion/ detorsion+single dose berberine (T/D+Bb), and torsion/detorsion+15 days berberine (T/D+15Bb). The torsion and detorsion model was applied in all non-sham groups. In the T/D+Bb group, a single dose of berberine was administered, while in the T/D+15Bb group, berberine was administered over a period of 15 days. After the rats were euthanized, their ovaries were excised. The left ovaries were used for histopathologic evaluation, which included ovarian injury scoring and follicle count, while the right ovaries were used for biochemical analyses (tissue transforming growth factor-β [TGF-β] and alpha-smooth muscle actin [α-SMA] levels). Results: The histopathologic evaluation scores for the ovaries were significantly lower in the T/D+B group (p<0.05) and the T/D+15B group (p<0.005) than in the T/D group. The follicle counts in the T/D group were lower than those in both the sham and treated groups (p<0.005). The TGF-β levels were significantly lower in the T/D+15B group (p<0.005), whereas the α-SMA levels did not show a significant difference. Conclusion: Both short- and long-term berberine use could potentially have therapeutic effects on ovarian torsion. Long-term berberine use exhibited anti-inflammatory effects by reducing TGF-β levels, thereby preventing ischemia-reperfusion injuries. Therefore, we suggest that long-term berberine use could be beneficial for ovarian torsion.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6935-6940
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• 2013

Background: This study aimed to develop a prognostic model in patients with early-stage cervical squamous cell carcinoma based on clinicopathological features, including invasive margin characteristics. Materials and Methods: Clinicopathological features and outcomes of 190 patients with FIGO stage IB-IIA cervical squamous cell carcinoma treated by surgery were collected and analyzed for factors associated with tumor recurrence. In addition to well-recognized pathological risk factors, the pathological characteristics of invasive margin (type of invasive pattern and degree of stromal desmoplasia and peritumoral inflammatory reaction) were also included in the analysis. Multiple scoring models were made by matching different clinicopathological variables and/or different weighting of the score for each variable. The model with the best performance in the prediction of recurrence and decreased survival was selected. Results: The model with the best performance was composed of a combined score of invasive pattern, lymphovascular space invasion (LVSI), and degree of inflammatory reaction and stromal desmoplasia (total score =10). Compared to those with score ${\leq}8$, the patients with score 9-10 had a significantly higher recurrence rate in the overall group (p<0.001) and the subgroup without adjuvant therapy (p<0.001), while the significance was marginal in the subgroup with adjuvant therapy (p=0.069). In addition, the patients with score 9-10 had a higher rate of tumor recurrence at distant sites (p=0.007). The disease-free survival was significantly lower in the patients with score 9-10 than those with score ${\leq}8$ among the overall patients (p<0.001), in the subgroup without adjuvant therapy (p<0.001), and the subgroup with adjuvant therapy (p=0.047). Conclusions: In this study, a prognostic model based on a combination of pathological characteristics of invasive margin and LVSI proved to be predictive of tumor recurrence and decreased disease-free survival in patients with early-stage cervical squamous cell carcinoma.

• Fire Science and Engineering
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• v.18 no.1
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• pp.54-66
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• 2004

In this article, we are to suggest the hazard-assessing method for the underground pipelines, and find out the pipeline-maintenance schemes of high efficiency in cost. Three kinds of methods are applied in order to refer to the approaching methods of listing the hazards for the underground pipelines: the first is RBI(Risk Based Inspection), which firstly assess the effect of the neighboring population, the dimension, thickness of pipe, and working time. It enables us to estimate quantitatively the risk exposure. The second is the scoring system which is based on the environmental factors of the buried pipelines. Last we quantify the frequency of the releases using the present THOMAS' theory. In this work, as a result of assessing the hazard of it using SPC scheme, the hazard score related to how the gas pipelines erodes indicate the numbers from 30 to 70, which means that the assessing criteria define well the relative hazards of actual pipelines. Therefore. even if one pipeline region is relatively low score, it can have the high frequency of leakage due to its longer length. The acceptable limit of the release frequency of pipeline shows 2.50E-2 to 1.00E-l/yr, from which we must take the appropriate actions to have the consequence to be less than the acceptable region. The prediction of total frequency using regression analysis shows the limit operating time of pipeline is the range of 11 to 13 years, which is well consistent with that of the actual pipeline. Concludingly, the hazard-listing scheme suggested in this research will be very effectively applied to maintaining the underground pipelines.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.