Objective: Chinese indigenous sheep breeds can be classified into the following three categories by their tail morphology: fat-tailed, fat-rumped and thin-tailed sheep. The typical sheep breeds corresponding to fat-tailed, fat-rumped, and thin-tailed sheep are large-tailed Han, Altay, and Tibetan sheep, respectively. Detection of copy number variation (CNV) and selection signatures provides information on the genetic mechanisms underlying the phenotypic differences of the different sheep types. Methods: In this study, PennCNV software and F-statistics (FST) were implemented to detect CNV and selection signatures, respectively, on the X chromosome in three Chinese indigenous sheep breeds using ovine high-density 600K single nucleotide polymorphism arrays. Results: In large-tailed Han, Altay, and Tibetan sheep, respectively, a total of six, four and 22 CNV regions (CNVRs) with lengths of 1.23, 0.93, and 7.02 Mb were identified on the X chromosome. In addition, 49, 34, and 55 candidate selection regions with respective lengths of 27.49, 16.47, and 25.42 Mb were identified in large-tailed Han, Altay, and Tibetan sheep, respectively. The bioinformatics analysis results indicated several genes in these regions were associated with fat, including dehydrogenase/reductase X-linked, calcium voltage-gated channel subunit alpha1 F, and patatin like phospholipase domain containing 4. In addition, three other genes were identified from this analysis: the family with sequence similarity 58 member A gene was associated with energy metabolism, the serine/arginine-rich protein specific kinase 3 gene was associated with skeletal muscle development, and the interleukin 2 receptor subunit gamma gene was associated with the immune system. Conclusion: The results of this study indicated CNVRs and selection regions on the X chromosome of Chinese indigenous sheep contained several genes associated with various heritable traits.
KSII Transactions on Internet and Information Systems (TIIS)
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v.10
no.11
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pp.5343-5364
/
2016
Considering the tradeoff between energy consumption and outage behavior in buffer-aided relay selection, a novel energy-efficient buffer-aided optimal relay selection scheme with power adaptation and Inter-Relay Interference (IRI) cancellation is proposed. In the proposed scheme, energy consumption minimization is the objective with the consideration of relay buffer state, outage probability and relay power control, in order to eliminate IRI. The proposed scheme selects a pair of optimal relays from multiple candidate relays, denoted as optimal receive relay and optimal transmit relay respectively. Source-relay and relay-destination communications can be performed within a time-slot, which performs as Full-Duplex (FD) relaying. Markov chain model is applied to analyze the evolution of relay buffer states. System steady state outage probability and achievable diversity order are derived respectively. In addition, packet transmission delay and power reduction performance are investigated with a specific analysis. Numerical results show that the proposed scheme outperforms other relay selection schemes in terms of outage behavior with power adaptation and IRI cancellation in the same relay number and buffer size scenario. Compared with Buffer State relay selection method, the proposed scheme reduces transmission delay significantly with the same amount of relays. Average transmit power reduction can be implemented to relays with the increasing of relay number and buffer size, which realizes the tradeoff between energy-efficiency, outage behavior and delay performance in green cooperative communications.
Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional $F_{ST}$ measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the $F_{ST}$ estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific $F_{ST}$ and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.
This study investigated relationships between the importance and satisfaction of rice-based menu selection attributes at family restaurants. For data collection, a total of 250 copies of questionnaires were distributed to 4-year college students who had an experience of a rice-based menu at casual dining restaurants, and finally 221 surveys (88.4%) among them were analyzed by using SPSS Win ver. 11.5. Twenty selection attributes were used to test the level of importance and satisfaction for rice-based menu. The factor analysis identified six dimensions of the importance of rice-based menu selection attributes; variety of items, menu information, recommendation & atmosphere, food quality, preferred menu, and price. Also, five dimensions of satisfaction were identified as nutrition & taste, menu information, preferred menu & atmosphere, variety of items, and cooking. Canonical correlation analysis revealed that preferred menu factor of importance was highly correlated with preferred menu and restaurant atmosphere factor of satisfaction of rice-based menu selection. The managerial implications of these results for rice-base menu selection attributes are as follows: There seems to be a need to develop a variety of rice-based menus, because rice-based menus tend to be considered as an additional menu, not a main course. Aggressive marketing and communication strategies are necessary to position rice-based menu as a main course for college students and as a major maket segment to family restaurants.
Beta-carotene producing transformants were produced in the background of 'Nagdongbyeo', a Japonica rice cultivar. Introgression of the carotenoid locus in the transformant, PAC4-2 into the elite cultivar 'Ilpumbyeo' was started. To initiate a backcrossing program, we surveyed 220 SSR markers and found that 38% of them were polymorphic between 'Ilpumbyeo' as a recurrent parent and the PAC4-2 as a recipient parent. The selection strategy comprising foreground and background selection was employed. First, foreground selection was practiced in $BC_1$, $BC_2$, and $BC_3$ generations using the transgene specific PCR-based marker in addition to visual scoring of the seed color. Marker-based background selection combined with phenotypic selection was employed from $BC_3F_2$ to $BC_3F_4$ generations. Blast search indicated that the transgene PAC4-2 was located between SSR markers, RM6 and RM482. 240 $BC_3F_3$ and 63 $BC_3F_4$ lines were evaluated for four agronomic traits including days to heading. Most of the lines were similar to Ilpumbyeo in agronomic traits evaluated. The percentage of PAC4-2 genome ranged from 4% to 21% with a mean of 12.5%, which was higher than the expected for an unselected $BC_3$ backcross population. This could be explained by the fact that two genes for beta-carotene and the stripe virus resistance were targeted in this study. We selected 10 representative $BC_3F_5$ lines from 63 $BC_3F_4$ lines based on agronomic traits and carotenoids content. The selection strategy would be appropriate for the introgression of beta-carotene gene in a breeding program.
Journal of The Korean Society of Integrative Medicine
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v.10
no.4
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pp.49-56
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2022
Purpose : The purpose of this study was to examine the effects of the motivation for choosing a major, COVID-19 anxiety, and work values on the employment preparation behavior of health college students and to provide evidence for developing programs for employment preparation behavior in the future. Methods : Employing a random sampling method, a survey was conducted from April 22 to June 3, 2022, using an electronically-disseminated questionnaire with college students majoring in medical technician, health administration, and nursing from D and K colleges located in Daegu. A total of 402 students who fully understood and agreed to the purpose of the study participated. The SPSS statistical program was used to analyze the collected data, which were verified using correlation and regression analyses. Results : The results of the study are: First, employment preparation behavior was positively correlated to major selection motivation, COVID-19 anxiety, and work values. Second, significant relationships were found between employment preparation behavior and motivation behind choosing a major, work values, and COVID-19 anxiety, in that order. The higher the major selection motivation, work values, and COVID-19 anxiety were, the better the employment preparation behavior was. Conclusion : The study's results indicate that it would be meaningful to provide health college students who were highly motivated to select their major and who possess sound work values with well-prepared job training programs. Various activities organized by the school for improving the students' self-satisfaction and self-efficacy, which can strengthen their long-term work values, could also be provided. In addition, due to the continuing COVID-19 pandemic, college students may feel anxious about new infectious diseases that might occur in the future. Therefore, considering the contemporary situation, a helpful educational program will be invaluable to fit the pupils for life's battle after they finish their education.
The purpose of this study was to examine the differences in clothing selection criteria and store selection criteria between each consumer groups by the preference for fast fashion. The data was collected from a questionnaire conducted on 317 female adults. The results were as follows. First, the factor analysis used to identify clothing selection criteria involved the following four factors: fashion, quality/practicality, status symbol, and economics. The consumer group preferring fast-fashion regarded fashion and economics as important factors and the non-preferring group regarded status symbol factor more. Second, five factors(atmosphere, product service/salesperson, shopping convenience, promotion/facilities) of store selection criteria were constructed by factor analysis, The consumer group preferring fast-fashion regarded atmosphere and product as important factors and the non-preferring group considered service/salesperson and promotion/facilities factors more. Third, the consumers who were of low age, low education, low income and unmarried preferred fast fashion brand.
Bsoul, Qusay;Abdul Salam, Rosalina;Atwan, Jaffar;Jawarneh, Malik
Journal of Information Science Theory and Practice
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v.9
no.4
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pp.15-34
/
2021
Text clustering is one of the most commonly used methods for detecting themes or types of documents. Text clustering is used in many fields, but its effectiveness is still not sufficient to be used for the understanding of Arabic text, especially with respect to terms extraction, unsupervised feature selection, and clustering algorithms. In most cases, terms extraction focuses on nouns. Clustering simplifies the understanding of an Arabic text like the text of the Quran; it is important not only for Muslims but for all people who want to know more about Islam. This paper discusses the complexity and limitations of Arabic text clustering in the Quran based on their themes. Unsupervised feature selection does not consider the relationships between the selected features. One weakness of clustering algorithms is that the selection of the optimal initial centroid still depends on chances and manual settings. Consequently, this paper reviews literature about the three major stages of Arabic clustering: terms extraction, unsupervised feature selection, and clustering. Six experiments were conducted to demonstrate previously un-discussed problems related to the metrics used for feature selection and clustering. Suggestions to improve clustering of the Quran based on themes are presented and discussed.
Kutubi, Abdullah Al Rahat;Hong, Min-Gee;Kim, Choen
Korean Journal of Remote Sensing
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v.34
no.1
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pp.151-166
/
2018
This paper compares the four selections of performance used in the application of genetic algorithms (GAs) to automatically optimize multispectral pixel cluster for unsupervised classification from KOMPSAT-3 data, since the selection among three main types of operators including crossover and mutation is the driving force to determine the overall operations in the clustering GAs. Experimental results demonstrate that the tournament selection obtains a better performance than the other selections, especially for both the number of generation and the convergence rate. However, it is computationally more expensive than the elitism selection with the slowest convergence rate in the comparison, which has less probability of getting optimum cluster centers than the other selections. Both the ranked-based selection and the proportional roulette wheel selection show similar performance in the average Euclidean distance using the pixel clustering, even the ranked-based is computationally much more expensive than the proportional roulette. With respect to finding global optimum, the tournament selection has higher potential to reach the global optimum prior to the ranked-based selection which spends a lot of computational time in fitness smoothing. The tournament selection-based clustering GA is used to successfully classify the KOMPSAT-3 multispectral data achieving the sufficient the matic accuracy assessment (namely, the achieved Kappa coefficient value of 0.923).
The purpose of this study was to analyze the correlation between radiation information sources and major selection satisfaction in radiologic science students of Korean and American. The subjects of this study were first-grade and second-grade at one university in Chungbuk, Korea and one university in Texas, USA. The survey study investigated from May 7, 2019 to May 28, 2019. As a result, first, these college students in both countries used the internet the most as them, but the percentage of information collected through textbooks was significantly higher among American college students. Second, Korean college students had a higher level of reliability in information sources than American college students in the order of internet, newspapers, and social network service (SNS), except government prints. Third, American college students had significantly higher satisfaction in major selection than Korean college students. Fourth, Korean college students were helped to select majors through various information sources, especially, the correlation coefficient between SNS was significantly higher.
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