• Title/Summary/Keyword: jackknife

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벼멸구 저항성 유전자에 대한 국내 벼멸구의 생물적 반응 연구 (Biological Response of Resistant Genes to Korean Brown Planthopper, Nilaparvata lugens Stål)

  • 최낙중;김광호;백채훈;이봉춘
    • 생명과학회지
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    • 제29권2호
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    • pp.202-208
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    • 2019
  • 벼멸구는 국내로 비래하여 벼에 가장 큰 피해를 주는 해충 중 하나이고, 매년 열대 및 아열대 지역에서 저기압 기류를 타고 침입한다. 따라서 벼멸구의 효과적인 방제를 위해 저항성 정도를 모니터링 하는 것은 매우 중요한 일이다. 국내 비래한 벼멸구를 지역별로 구분하여 벼멸구 저항성 유전자(Bph1, Bph2, Bph18)에 각각 접종하여 사육실의 동일한 환경조건($25{\pm}2^{\circ}C$, $60{\pm}5%\;RH$, L:D=16:8)에서 벼멸구의 감로 배설, 발육기간 및 산자수 등을 조사하였다. 얻어진 정보는 Jackknife 방법을 이용하여 생명표를 작성하였다. 벼멸구 저항성 유전자 중 Bph1 유전자에서 감로 분비량이 가장 적었고, 약충 발육기간은 $13.7{\pm}0.10$일(Bph2, 남해, 2015)에서 $18.5{\pm}1.06$일(Bph2, 사천, 2016)로 나타났다. 산란기간과 암컷수명은 감수성, Bph2 및 Bph18 (1980s 예외)에서 긴 것으로 조사되었고, 산자수도 2개의 동일한 저항성 유전자에서 많이 관찰되었다. 순증가율($R_0$)은 Bph2 유전자에서 지역에 관계없이 높은 것으로 나타났는데 내적자연증가율($r_m$)은 저항성 유전자에 대해 지역별로 차이를 보였다. 생명표는 벼멸구가 매년 다른 지역에서 비래하거나 그 생물적 특징이 다르다는 것을 보여준다.

차세대 염기서열 분석법을 이용한 된장과 간장의 미생물 분포 및 바이오마커 분석 (Comparative Microbiome Analysis of and Microbial Biomarker Discovery in Two Different Fermented Soy Products, Doenjang and Ganjang, Using Next-generation Sequencing)

  • 하광수;정호진;노윤정;김진원;정수지;정도연;양희종
    • 생명과학회지
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    • 제32권10호
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    • pp.803-811
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    • 2022
  • 우리나라 전통 콩 발효식품은 탄수화물을 주식으로 하는 한국인의 식생활에 중요한 단백질 급원임에도 불구하고 콩 발효식품의 미생물 다양성과 군집 구조에 대해서는 거의 알려진 바가 없다. 본 연구는 16S rDNA 유전자 서열 분석 기반의 차세대 염기서열 분석법을 이용하여 한국 전통 발효식품인 된장과 간장의 미생물 군집 구조를 밝히고자 하였다. Alpha-diversity 분석 결과 미생물 다양성 지표인 Shannon과 Simpson에서 된장과 간장의 미생물 다양성에 통계학적인 차이가 있는 것으로 나타났으나, 종 풍부도 지표인 ACE, CHAO, Jackknife에서는 차이가 없는 것으로 나타났다. 된장과 간장의 미생물 분포 분석 결과 된장과 간장의 공통적인 우점균은 Firmicutes로 나타났으나, 속 수준에서의 미생물 분포를 분석한 결과 된장에서 Bacillus, Kroppenstedtia, Clostridium, Pseudomonas가 간장보다 높은 비율을 차지하고 있는 것으로 나타났으며, 간장에서는 Tetragenococcus, Chromhalobacter, Lentibacillus, Psychrobacter와 같은 호염성 또는 내염성 세균이 된장보다 높은 비율을 차지하는 것으로 나타났다. 된장과 간장의 미생물 군집구조에 통계학적인 차이가 있는지 확인하기 위해 paired-PERMANOVA 분석을 수행하였으며, 그 결과 통계학적으로 매우 유의한 수준의 차이가 있는 것으로 나타났다. 된장과 간장의 미생물 군집구조 차이에 큰 영향을 미치는 biomarker를 분석하기 위해 LEfSe 분석을 수행하였으며, 그 결과 Bacillus와 Tetragenococcus가 된장과 간장의 미생물 군집 구조에 차이를 나타내는 biomarker로 분석되었다.

GIS를 이용한 강하분진 중 금속원소의 공간분포분석 (Spatial Distribution Analysis of Metallic Elements in Dustfall using GIS)

  • 윤훈주;김동술
    • 한국대기환경학회지
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    • 제13권6호
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    • pp.463-474
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    • 1997
  • Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

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연결(連結) 차량(車輛)의 재크나이프 현상에 영향(影響)을 미치는 인자(因子)인자에 대한 연구 (A Study on the Factors that Influence Jack Knife Phenomenon of Articulated Vehicles)

  • 강대민;안승모
    • 동력기계공학회지
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    • 제11권2호
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    • pp.58-63
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    • 2007
  • Vehicular safety and occupant injury have been of considerable interest to the public. The dynamic response of an articulated vehicle is different from that of single body vehicle due to its geometric and inertia properties. Articulated vehicles have the tendency to jackknife if they lose driving safety. Influence of factors for driving safety of an articulated vehicle(Tractor-Semitrailers) has been analysed by the EDVTS, a kinetic analysis program for an articulated vehicle. EDVTS permits an analyst to investigate the effect of many variables in a short period of time, and enables to obtain an accurate explanation of driving safety. The factors used in the analysis include the load, friction coefficient, tire flat, increase of braking force, and trailer geometry. Based on the results, the articulation angle and driving safety were influenced remarkably by the load, coefficient of friction, increase of braking force. However, trailer geometry, such as length and width, did not affect articulation angle and driving safety

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Practice of causal inference with the propensity of being zero or one: assessing the effect of arbitrary cutoffs of propensity scores

  • Kang, Joseph;Chan, Wendy;Kim, Mi-Ok;Steiner, Peter M.
    • Communications for Statistical Applications and Methods
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    • 제23권1호
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    • pp.1-20
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    • 2016
  • Causal inference methodologies have been developed for the past decade to estimate the unconfounded effect of an exposure under several key assumptions. These assumptions include, but are not limited to, the stable unit treatment value assumption, the strong ignorability of treatment assignment assumption, and the assumption that propensity scores be bounded away from zero and one (the positivity assumption). Of these assumptions, the first two have received much attention in the literature. Yet the positivity assumption has been recently discussed in only a few papers. Propensity scores of zero or one are indicative of deterministic exposure so that causal effects cannot be defined for these subjects. Therefore, these subjects need to be removed because no comparable comparison groups can be found for such subjects. In this paper, using currently available causal inference methods, we evaluate the effect of arbitrary cutoffs in the distribution of propensity scores and the impact of those decisions on bias and efficiency. We propose a tree-based method that performs well in terms of bias reduction when the definition of positivity is based on a single confounder. This tree-based method can be easily implemented using the statistical software program, R. R code for the studies is available online.

개선된 PRISM 모형을 이용한 고해상도 일강수량 추정 (Estimation of High Resolution Daily Precipitation Using a Modified PRISM Model)

  • 김종필;이우섭;조현곤;김광섭
    • 대한토목학회논문집
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    • 제34권4호
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    • pp.1139-1150
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    • 2014
  • 본 연구에서는 M-PRISM 모형을 이용하여 $1km{\times}1km$ 공간해상도 일강수량 추정에 대한 적용성을 검토하였다. 또한 회귀모형을 이용하여 M-PRISM 모형 매개변수를 추정하였으며, 잭나이프 방법을 이용하여 모형을 검증하였다. 기상청 385개 강수 관측지점에 대하여 M-PRISM을 이용하여 일강수량을 추정하고 PRISM 모형과 비교하였다. 비교결과, 강수의 정량적 크기를 추정에서는 두 모형에서 뚜렷한 차이를 찾아볼 수 없었으나, 강수의 발생빈도 추정에 있어서는 M-PRISM 모형이 더 우수한 결과를 나타내었다. 따라서 본 연구에서 제안한 M-PRISM 모형은 고해상도의 일강수량을 추정함에 있어서 매우 유용하게 사용될 수 있을 것으로 판단된다.

Prediction of subcellular localization of proteins using pairwise sequence alignment and support vector machine

  • Kim, Jong-Kyoung;Raghava, G. P. S.;Kim, Kwang-S.;Bang, Sung-Yang;Choi, Seung-Jin
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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    • pp.158-166
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    • 2004
  • Predicting the destination of a protein in a cell gives valuable information for annotating the function of the protein. Recent technological breakthroughs have led us to develop more accurate methods for predicting the subcellular localization of proteins. The most important factor in determining the accuracy of these methods, is a way of extracting useful features from protein sequences. We propose a new method for extracting appropriate features only from the sequence data by computing pairwise sequence alignment scores. As a classifier, support vector machine (SVM) is used. The overall prediction accuracy evaluated by the jackknife validation technique reach 94.70% for the eukaryotic non-plant data set and 92.10% for the eukaryotic plant data set, which show the highest prediction accuracy among methods reported so far with such data sets. Our numerical experimental results confirm that our feature extraction method based on pairwise sequence alignment, is useful for this classification problem.

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黃砂의 量的推定을 위한 基礎硏究 (Basic Research on the Quantitative Estimation of Yellow Sand)

  • 김동술
    • 한국대기환경학회지
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    • 제6권1호
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    • pp.11-21
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    • 1990
  • To quantitatively estimate the effect of yellow sand(loess) fromt he Northern China, various soil sources having similar chemical compositions to yellow sands should be separated and identified. After that, mass contribution for yellow sand can be calculated. The study showed that it was impossible to solve this problem by the traditional bulk analyses. However, particle-by-particle analysis by a CCSEM (computer controlled scanning electron microscope) gave enormous potentials to solve it. To perform this study, seven soil source data analyzed by CCSEM were obtained from Texas, U.S.A. Initially, each soil date was classified into two groups, coarse and fine particle groups since the particle number distribution showed a minimum occurring at 5.2$\mu$m of aerodynamic diameter. Particles in each group were then classified into one of the 283 homogeneous particle classes by the universal classification rule which had been built by an expert system in the early study. Further, mass fractions and their uncertainties for each class in each source were calculated by the Jackknife method, and then source profile matrix for the 7 soil sources was created. To use the profile matrix in the study of source contribution, it is necessary to test the degree of collinearity among sources. The profiles were tested by the singular value decomposition method. As a result, each soil source characterized by artificially created variables was totally independent each other and is ready to use in source contribution studies as a receptor model.

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Effect of Herbicide Combinations on Bt-Maize Rhizobacterial Diversity

  • Valverde, Jose R.;Marin, Silvia;Mellado, Rafael P.
    • Journal of Microbiology and Biotechnology
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    • 제24권11호
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    • pp.1473-1483
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    • 2014
  • Reports of herbicide resistance events are proliferating worldwide, leading to new cultivation strategies using combinations of pre-emergence and post-emergence herbicides. We analyzed the impact during a one-year cultivation cycle of several herbicide combinations on the rhizobacterial community of glyphosate-tolerant Bt-maize and compared them to those of the untreated or glyphosate-treated soils. Samples were analyzed using pyrosequencing of the V6 hypervariable region of the 16S rRNA gene. The sequences obtained were subjected to taxonomic, taxonomy-independent, and phylogeny-based diversity studies, followed by a statistical analysis using principal components analysis and hierarchical clustering with jackknife statistical validation. The resilience of the microbial communities was analyzed by comparing their relative composition at the end of the cultivation cycle. The bacterial communites from soil subjected to a combined treatment with mesotrione plus s-metolachlor followed by glyphosate were not statistically different from those treated with glyphosate or the untreated ones. The use of acetochlor plus terbuthylazine followed by glyphosate, and the use of aclonifen plus isoxaflutole followed by mesotrione clearly affected the resilience of their corresponding bacterial communities. The treatment with pethoxamid followed by glyphosate resulted in an intermediate effect. The use of glyphosate alone seems to be the less aggressive one for bacterial communities. Should a combined treatment be needed, the combination of mesotrione and s-metolachlor shows the next best final resilience. Our results show the relevance of comparative rhizobacterial community studies when novel combined herbicide treatments are deemed necessary to control weed growth.

Reexamination of Estimating Beta Coecient as a Risk Measure in CAPM

  • Phuoc, Le Tan;Kim, Kee S.;Su, Yingcai
    • The Journal of Asian Finance, Economics and Business
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    • 제5권1호
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    • pp.11-16
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    • 2018
  • This research examines the alternative ways of estimating the coefficient of non-diversifiable risk, namely beta coefficient, in Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964) that is an essential element of assessing the value of diverse assets. The non-parametric methods used in this research are the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator). The Jackknife, the resampling technique, is also employed to validate the results. According to finance literature and common practices, these coecients have often been estimated using Ordinary Least Square (LS) regression method and monthly return data set. The empirical results of this research pointed out that the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) performed much better than Ordinary Least Square (LS) in terms of eciency for large-cap stocks trading actively in the United States markets. Interestingly, the empirical results also showed that daily return data would give more accurate estimation than monthly return data in both Ordinary Least Square (LS) and robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) regressions.