• Title/Summary/Keyword: non-nested tests

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Development of Nested PCR Primer Set for the Specific and Highly Sensitive Detection of Human Parvovirus B19

  • Cho, Kyu-Bong
    • Biomedical Science Letters
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    • v.24 no.4
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    • pp.390-397
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    • 2018
  • For the specific detection of human Parvovirus B19 (HuPaV-B19), we designed ten specific PCR primers from 3,800~4,500 nucleotides of HuPaV-B19 complete genome (NC_000883.2). Seventeen candidate PCR primer sets for specific detecting HuPaV-B19 were constructed. In specific reaction of HuPaV-B19, seventeen PCR primer sets showed specific band, however five PCR primer sets were selected basis of band intensity, amplicon size and location. In non-specific reaction with seven reference viruses, four PCR primer sets showed non-specific band, however one PCR primer set is not. Detection sensitivity of final selective PCR primer set was $100fg/{\mu}L$ for 112 minute, and PCR amplicon is 539 base pairs (bp). In addition, nested PCR primer set was developed, for detection HuPaV-B19 from a low concentration of contaminated samples. Selection of nested PCR primer set was basis of sensitivity and groundwater sample tests. Detection sensitivity of final selective PCR and nested PCR primer sets for the detection of HuPaV-B19 were $100fg/{\mu}L$ and $100ag/{\mu}L$ basis of HuPaV-B19 plasmid, it was able to rapid and highly sensitive detection of HuPaV-B19 than previous reports. We expect developed PCR primer set in this study will used for detection of HuPaV-B19 in various samples.

Nonlinearities and Forecasting in the Economic Time Series

  • Lee, Woo-Rhee
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.931-954
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    • 2003
  • It is widely recognized that economic time series involved not only the linearities but also the non-linearities. In this paper, when the economic time series data have the nonlinear characteristics we propose the forecasts method using combinations of both forecasts from linear and nonlinear models. In empirical study, we compare the forecasting performance of 4 exchange rates models(AR, GARCH, AR+GARCH, Bilinear model) and combination of these forecasts for dairly Won/Dollar exchange rates returns. The combination method is selected by the estimated individual forecast errors using Monte Carlo simulations. And this study shows that the combined forecasts using unrestricted least squares method is performed substantially better than any other combined forecasts or individual forecasts.