• 제목/요약/키워드: Tripartite specific relations

검색결과 2건 처리시간 0.014초

Biological Application of Two Protozoan Species, Euplotes sp. and Vorticella sp., for the Stable Culture of the Rotifer Brachionus rotundiformis in Laboratory Experiments of Inter- and Tripartite-Specific Relations

  • Jung, Min-Min
    • Fisheries and Aquatic Sciences
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    • 제15권3호
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    • pp.209-213
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    • 2012
  • Members of the ciliate group of protozoans are often observed in mass cultures of rotifers. In particular, Euplotes and Vorticella are common contaminating species. In this study, I examined the effect of the ciliates Euplotes sp. and Vorticella sp. on the growth of the rotifer Brachionus rotundiformis by conducting inter-specific and tripartite-specific mixed-culture experiments. The growth of rotifers was suppressed in co-existence with Euplotes sp. compared with monocultures of rotifers. However, Vorticella sp. promoted rotifer growth. Moreover, Vorticella sp. improved the growth of rotifers suppressed by Euplotes sp. contaminants. In 5-L semi-mass cultures of rotifers, growth of the contaminating protozoan Euplotes sp. was heavily suppressed by Vorticella sp. The stable maintenance of the rotifer culture ecosystem can be achieved by manipulating the types of contaminating protozoan species.

탐색적 확인적 요인 분석을 통한 "과학에 대한 태도" 3요소 모델의 타당도 연구 (A Study of Validity in Tripartite Model of "Attitudes towards Science" using Exploratory and Confirmatory Factor Analyses)

  • 이경훈
    • 한국과학교육학회지
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    • 제17권4호
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    • pp.481-492
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    • 1997
  • The purpose of this study is to construct validity of Tripartite model of "Attitudes towards Science" using Exploratory and Confirmatory Factor Analyses. Exploratory and confirmatory factor analyses are two major approaches to factor analysis. The primary goal of factor analysis is to explain the covariances or correlations between many observed variables by means of relatively few underlying latent variables. In exploratory factor analysis, the number of latent variables is not determined before the analysis, all latent variables typically influence all observed variables, the measurement errors(${\delta}$) are not allowed to correlate, and unidentification of parameters is common. Confirmatory factor analysis requires a detailed and identified initial model. Confirmatory factor analysis techniques allow relations between latent and observed variables that are not possible with traditional, exploratory factor analysis techniques. As a result of exploratory factor analysis, tripartite model of "Attitudes towards Science" being composed of affection, behavioral intention and cognition is empirically identified. But attitude of science career being composed of affection and behavioral intention is identified. In validity test using confirmatory factor analysis, measurement structure of Tripartite model of "Attitudes towards Science" is not correspondent to data set. Because it is concluded that the object of attitudes are not specific.

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