To estimate the genetic characteristics and cumulative power of discrimination (CPD) within Korean native commercial chicken, we used a total of 395 genomic DNAs from six breeds population (Korean Native Red chicken: R, Korean Native Yellow chicken: Y, Korean native Commercial Chicken: C, Ogal chicken: S, Hy-Line Brown: H, White Leghorn: W). Genetic diversity indices including mean allele number among loci, unbiased heterozygosity ($h_i$) within locus, effective number of alleles ($N_e$) and polymorphism information content (PIC) as well as the unbiased average heterozygosity (H) among loci in the populations were calculated using the generated allele frequencies by each marker. Frequencies of microsatellites markers were used to estimate heterozygosities and genetic distances. The nearest distance (0.119) was observed between the C and Y strains. The generated unbiased average heterozygosity among loci in each population was integrated to the global formula of CPD and the result demonstrated that the CPD within the six chicken populations was 99.461%.
Various competencies such as critical thinking, systems thinking, problem solving competence, communication skill, and data literacy are likely to be required in the 4th industrial revolution. The competency regarding data literacy is one of those competencies. To nurture citizens who will live in the future, it is timely to consider research on teacher education for supporting teachers' development of statistical thinking as well as statistical knowledge. Therefore, in this study we developed and implemented a data analysis project for pre-service teachers to understand their changes in statistical knowledge in addition to their experiences of data-driven decision making process that required them utilizing their statistical thinking. We used a mixed method (i.e., sequential explanatory design) research to analyze the quantitative and qualitative data collected. The findings indicated that pre-service teachers have low knowledge level of their understanding on the relationship between population means and sample means, and estimation of the population mean and its interpretation. When it comes to the data-driven decision making process, we found that the pre-service teachers' experiences varied even when they worked as a small group for the project. We end this paper by presenting implications of the study for the fields of teacher education and statistics education.
A trial has been made to find out a new method of calculating the survival rate of a fish Population utilizing the length composition data and the characteristics of the frequency curve of the length which usually is normal distribution curve. In this paper, a stochastic method is introduced and applied to calculate the survival rate of yellow croaker caught by Korean trawlers in the Yellow Sea and the East China Sea in 1971. The results are as follows : Mean of survival rate 0.46089 Variance 0.03073 Standard deviation 0.17529 95 percent confidence interval 0.36040-0.56138.
This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.
To estimate level of genetic variation and genetic differentiation among populations of 3 populations in Abies koreana and 5 populations in Abies nephrolepis, 5 nSSR markers were analyzed. Except 1 locus where too many alleles were observed excessively, population genetic parameters were recalculated with 4 loci. Mean expected heterozygosities ($H_e$) were 0.292 in A. koreana and 0.220 in A. nephrolepis, respectively. In both species, positive fixation coefficient was estimated (F=0.065 for A. koreana and F=0.095 for A. nephrolepis), which suggests that there is an excess of homozygotes relative to Hardy-Weinberg expectations within populations. Relatively high degree of population differentiation was observed in A. koreana ($F_{ST}=0.063$). compared to that of A. nephrolepis ($F_{ST}=0.039$). From 3-level Hierarchical estimation of F-staticstics, only 4.9% of the genetic variation was allocated between species ($F_{PT}$), which suggested that most of genetic variation was shared between two species. On the basis of results from analysis of genetic relationships among populations, 2 populations of A. koreana (Mt. Halla and Mt. Deogyu) were genetically distinct from the populations of A. nephrolepis but a population of Mt. Jiri was allocated within a group of populations of A. nephrolepis. Populations of both species seemed to have undergone genetic drift due to gradual decrease in population size induced by global warming after the last glacier, which resulted in increase of homozygotes by inbreeding. It could be also postulated that these species might be diverged recently and It is likely that the two species have not fully speciated yet.
Journal of Korean Society of Occupational and Environmental Hygiene
/
v.15
no.2
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pp.124-134
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2005
To investigate the exposure effect of polynuclear aromatic hydrocarbons (PAHs), we measured airborne total PAHs as an external dose, urinary 1-hydroxypyrene (1-OHP) as an internal dose of PAHs exposure, and analyzed the relationship between urinary 1-OHP concentration and PAHs exposure. The study population contained 44 workers in steel-pipe coating and paint manufacture industries. The airborne PAHs was obtained during survey day, and urine were sampled at the end of shift. Personal information on age, body weight, height, eniployment duration, smoking habit, and alcohol consumption was obtained by a structured questionnaire. Airborne PAHs were analyzed by the gas chromatograph with mass selective detector. Urinary 1-OHP levels were analyzed by the high performance liquid chromatograph with ultraviolet wavelength detector. For statistical estimation, t-test, ${\chi}^2$-test, analysis of variance, correlation analysis, arid regression analysis were executed by SPSS/PC (Windows version 10). The mean of environmental total PAHs was $87.8{\pm}7.81{\mu}g/m^3$. The mean concentration ($526.5{\pm}2.85{\mu}g/m^3$) of workers in steel-pipe coating industries using coal tar enamel was the higher than that ($17.5{\pm}3.36{\mu}g/m^3$) of workers in paint manufacture industries using coal tar paint. The mean of urinary 1-OHP concentration ($51.63{\pm}3.144{\mu}\;mol/mol$ creatinine) of workers in steel-pipe coating industries was the higher than that ($2.33{\pm}4.709{\mu}\;mol/mol$ creatinine) of workers in paint manufacture industries. The mean of urinary 1-OHP concentration of smokers was the higher than that of non-smokers. There was significant correlation between the urinary concentration of 1-OHP and the environmental concentration of PAHs (r=O.S48, p<0.001), pyrene(r=0.859, p<0.001), and urinary cotinine (r=0.324, p<0.05). The regression equation between the urinary concentration of 1-OHP in ${\mu}g/g$ creatinine($C_{1-OHP}$) and airborne concentration of PAHs (or pyrene) in ${\mu}g/m^3$ ($C_{PAHs}$ or Cpyrene) is: Log ($C_{1-OHP}$)=-0.650+0.889×Log($C_{PAHs}$), where $R^2=0.694$ and n=38 for p<0.001.Log ($C_{1-OHP}$)=1.087+0.707${\times}$Log(Cpyrene), where $R^2=0.713$ and n=38 for p<0.001. From the results of stepwise multiple regression analysis about 1-OHP, significant independents were total PAHs and urinary cotinine (adjusted $R^2=0.743$, p<0.001). In this study, there were significant correlation between the urinary concentration of 1-OHP and the airborne concentration of PAHs. The urinary 1-OHP was effective index as a biomarker of airborne PAHs in workplace. But it was influenced by non-occupational PAHs source, smoking.
Bioelectrical impedance analysis (BIA) models must be validated against a reference method in a representative population sample before they can be accepted as accurate and applicable. The purpose of this study was to compare the eight-electrode BIA method with DEXA as a reference method in the assessment of body composition in Korean adults and to investigate the predictive accuracy and applicability of the eight-electrode BIA model. A total of 174 apparently healthy adults participated. The study was designed as a cross-sectional study. FM, %fat, and FFM were estimated by an eight-electrode BIA model and were measured by DEXA. Correlations between BIA_%fat and DEXA_%fat were 0.956 for men and 0.960 for women with a total error of 2.1%fat in men and 2.3%fat in women. The mean difference between BIA_%fat and DEXA_%fat was small but significant (P < 0.05), which resulted in an overestimation of $1.2{\pm}2.2$%fat (95% CI: -3.2-6.2%fat) in men and an underestimation of $-2.0{\pm}2.4$%fat (95% CI: -2.3-7.1%fat) in women. In the Bland-Altman analysis, the %fat of 86.3% of men was accurately estimated and the %fat of 66.0% of women was accurately estimated to within 3.5%fat. The BIA had good agreement for prediction of %fat in Korean adults. However, the eight-electrode BIA had small, but systemic, errors of %fat in the predictive accuracy for individual estimation. The total errors led to an overestimation of %fat in lean men and an underestimation of %fat in obese women.
Lee, Jeeyeon;Kwon, Sung Ok;Yeoh, Yoonjae;Seo, Min Jeong;Lee, Gae Ho;Kim, Cho-il
Korean Journal of Community Nutrition
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v.27
no.3
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pp.245-253
/
2022
Objectives: This study was conducted to find out if the dietary iron intake of Koreans estimated by 2 different methods (iron content sources) using the food intake data from the Korea National Health and Nutrition Examination Survey (KNHANES) are comparable. One method was based on the KNHANES's Food & Nutrient Database (FND) derived mainly from the Korean Food Composition Table and the other used the iron content (IC) of food samples processed in the Korean Total Diet Study (KTDS). Methods: Dietary intake data from the 2013-2016 KNHANES was used to select representative foods (RFs) in KTDS for iron analysis. Selection of the RFs and cooking methods for each RF (RF × cooking method pair) was performed according to the 'Guidebook for Korean Total Diet Studies' and resulted in a total of 132 RFs and 224 'RF × cooking method' pairs. RFs were collected in 9 metropolitan cities nationwide once or twice (for those with seasonality) in 2018 and made into 6 composites each, based on the origin and season prior to cooking. Then, the RF composites prepared to a 'table ready' state for KTDS were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Dietary iron intake of the Korean population was estimated using only RFs' intake data based on the 2 sources of iron content, namely FND-KNHANES and IC-KTDS. Results: RFs in KTDS covered 92.0% of total food intake of Koreans in the 2016-2018 KNHANES. Mean iron intake of Koreans was 7.77 mg/person/day by IC-KTDS vs 9.73 mg/person/day by FND-KNHANES. The major food groups contributing to iron intake were meats (21.7%), vegetables (20.5%), and grains & cereals (13.4%) as per IC-KTDS. On the other hand, the latter source (FND-KNHANES) resulted in a very different profile: grains & cereals (31.1%), vegetables (16.8%), and meats (15.3%). While the top iron source was beef, accounting for 8.6% in the former, it was polished rice (19.2%) in the latter. There was a 10-fold difference in the iron content of polished rice between 2 sources that iron intakes excluding the contribution by polished rice resulted in very similar values: 7.58 mg/person/day by IC-KTDS and 7.86 mg/person/day by FND-KNHANES. Conclusions: This study revealed that the dietary iron intake estimated by 2 different methods were quite comparable, excluding one RF, namely polished rice. KTDS was thus proven to be a useful tool in estimating a 'closer-to-real' dietary intake of nutrients for Koreans and further research on various nutrients is warranted.
We aimed to estimate the accumulated degree days required for the development of $Cloeon$$dipterum$ (Ephemeroptera: Baetidae) in an experimental tub under field conditions from August 7 to October 10 in 2011. After 4 days in a tub setting, a dead female adult was found on the water surface at which oviposition had presumably occurred. Adults emerged from 39 days to 61 days after the oviposition date. The total number of emerged adults was 229, and the sex ratio (number of females : total population) was 0.45, although not statistically significant ($p$ >0.05). The males generally emerged earlier than females. Assuming that the basal temperature ($T_b$) value is $0^{\circ}C$, we estimated the number of accumulated degree days required for the development of $C.$$dipterum$ to be $1,221.8{\pm}116.0$ DD (mean${\pm}$SD). Since the annual number of accumulated degree days in the reference wetland was measured to be 5,650.0 DD, we estimated that $C.$$dipterum$ is multivoltine, with a maximum of 4 cohorts in 1 year in natural habitats.
In the current society, where statistical literacy is recognized as an important ability, statistical education utilizing the statistical problem solving, a series of processes for performing statistics, is required. The result interpretation stage is especially important because many forms of statistics we encounter in our daily lives are the information from the analysis results. In this study, data on private education were provided to pre-service mathematics teachers, and a project was carried out in which they could experience a statistical problem solving process using the population mean estimation. Therefore, this study analyzed the characteristics shown by pre-service mathematics teachers during the result interpretation stage. First, many pre-service mathematics teachers interpreted results based on the data, but the inference was found to be a level of 2 which is not reasonable. Second, pre-service mathematics teachers in this study made various kinds of decisions related to public education, such as improving classes and after-school classes. In addition, the pre-service mathematics teachers in this study seem to have made decisions based on statistical analysis results, but they made general decisions that teachers could make, rather than specifically. Third, the pre-service mathematics teachers of this study were reflective about the question formulation stage, organizing & reducing data stage, and the result interpretation stage, but no one was reflective about the result interpretation stage.
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