• 한국환경농학회지
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• 제30권4호
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• pp.466-472
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• 2011

본 연구는 국내에서 개발된 형질전환 콩 재배 시 토양 미생물 군집에 미치는 영향과 수평적 유전자 이동 여부를 알아보기 위해 수행되었다. 성숙기 토양의 미생물 군집밀도의 경우 형질전환 콩 근권 토양 미생물 군집밀도가 비 형질전환 콩 근권 토양과 유사하여 형질전환 콩 재배가 근권 토양 미생물에 영향을 미치지 않는 것으로 나타났다. 근권 토양의 우점 미생물 분포 양상 분석 결과, Proteobacteria, Firmicutes와 Actinobacteria 순으로 나타났으며 점유율은 다소 차이를 보였으나 우점종은 거의 유사하였다. 근권 토양 DNA에 대한 DGGE 분석 결과, 형질전환 콩과 비 형질전환 콩의 근권 토양 미생물 군집의 변화는 보이지 않았다. 형질전환 콩 재배에 따른 토양의 화학성을 분석한 결과, 형질전환 콩과 비 형질전환 콩의 근권 미생물상의 명확한 차이가 나타날 정도로 토양간 화학성의 차이는 크지 않았다. 형질전환 작물에 도입된 유전자군을 대상으로 식물체와 근권 토양 DNA에 대한 PCR 분석을 수행한 결과 수평적 유전자 이동성은 일어나지 않은 것으로 추정되었다.

• 대한약리학회지
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• 제31권2호
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• pp.241-250
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• 1995

Protein B23 is one of the major nucleolar phosphoproteins associated with pre-ribosomal particles, and is localized in the granular region of the nucleolus. Recent studies suggest that protein B23 shuttles between nucleus and cytoplasm and also interacts with HIV Rev. These findings indicate that protein B23 is important in nucleocytoplasmic relationship and viral replication. However, the exact function of protein B23 is not clear yet. In acute nucleolar hypertrophy of rat liver, treated with thioacetamide, there was observed an increase of not only protein B23 but also B23-like protein p45 when anti-B23 monoclonal antibody (MAb) was used for identification. On the basis of the large B23 specific epitope structure composed of 68 amino acids, a hypothesis was formulated to examine that p45 is the pre-B23 resulting from excessive production of B23. In an attempt to investigate the precursor of B23, we analyzed the subcellular fractions and microsomal subfractions. Subsequently, we analyzed the finger printings of B23-like proteins using the tryptic peptide mapping. The results are summarized: 1) Using B23 MAb, we observed the presence of B23-like proteins in nucleolar fraction, nucleoplasmic fraction and microsomal fraction. 2) In the further microsomal subfractionation, we could partially purify B23-like protein in 2M layer of sucrose gradient. 3) When ion exchange chromatography was employed, there were protein species 80kDa(p80), 65kDa(p65) and 60kDa(p60). 4) Based on the tryptic map analysis of $^{125}I$ labeled proteins, the similarity between B23 and p80 was found only in 9 out of 14(B23) and 21(p80) peptides, and difference was found in the remaining peptides. p80 and p60 had 18 common peptides, and all the peptides of p60 were similar to those of p80. From these results, it is proposed that p45 is an abnormal metabolite resulting from carcinogenesis by thioacetamide, and it is not the precursor of B23. In addition, we suggest that p80 may be a precursor of p45.

• 대한방사선기술학회지:방사선기술과학
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• 제21권1호
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• pp.35-39
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• 1998

We analyzed image factors to determine the characteristic factors that need for intelligent replenishment system of the auto film processor. We processed the serial 300 sheets of radiographic films of chest phantom without replenishment of developing and fixation replenisher. We took the digital data by using film digitizer which scaned the films and automatically summed up the pixel values of the films. We analyzed characteristic curves, average gradients and relative speeds of individual film using densitometer and step densitometry. We also evaluated the pH of developer, fixer, and washer fluid with digital pH meter. Fixer residual rate and washing effect were measured by densitometer using the reagent methods. There was no significant reduction of the digital density numbers of the serial films without replenishment of developer and fixer. The average gradients were gradually decreased by 0.02 and relative speeds were also gradually decreased by 6.96% relative to initial standard step-densitometric measurement. The pHs of developer and fixer were reflected the inactivation of each fluid. The fixer residual rates and washing effects after processing each 25 sheets of films were in the normal range. We suggest that the digital data are not reliable due to limitation of the hardware and software of the film digitizer. We conclude that average gradient and relative speed which mean the film's contrast and sensitivity respectively are reliable factors for determining the need for the replenishment of the auto film processor. We need more study of simpler equations and programming for more intelligent replenishment system of the auto film processor.

• 응용통계연구
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• 제30권1호
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• pp.25-39
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• 2017

최근 경륜은 2015년도 기준, 5백만 명 이상의 많은 사람들이 참여하고 2조를 넘어선 매출을 발생시키는 대중적인 레저스포츠로서 자리 잡고 있다. 본 연구의 목적은 다양한 통계적 분석기법을 사용하여 경륜경기의 순위를 예측하고, 순위에 유의한 영향을 미치는 변수들을 파악하는 데에 있다. 다양한 Classification 방법과 Regression 방법들을 적용하여 순위예측모형을 만들고 비교분석하였다. 대부분의 모형에서 공통적으로 선택된 변수들을 살펴보면, 등급이 강급될수록, 종합득점이 높을수록 순위가 높아지며 반대로 등급이 승급될수록, 번호 4번을 부여받을수록 그리고 최근성적의 순위가 낮을수록 순위가 낮아지는 것을 알 수 있었다. 또한, 선수의 실력과 관련된 연속형 변수들을 각 경기별로 평균값을 빼서 보정한 자료와 원자료를 사용하여 모형을 적합시킨 결과 모든 모형에서 보정된 자료를 사용하였을 때 더 낮은 오분류율을 보였다. 마지막으로 분석에 사용하지 않은 최근 한 달 경기결과를 예측해서 베팅했을 때 모든 경우에 예측률은 높았지만 큰 이익을 거두지 못했는데 그 이유는 낮은 배당률을 가진 경기의 결과만을 잘 예측했기 때문이다.

• ALGAE
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• 제32권1호
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• pp.57-66
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• 2017

The red alga Gracilaria vermiculophylla, a species native to the waters of Korea and Japan, has invaded marine coastal areas of Europe and the Americas, thriving in conditions that differ from those of its native habitat. In recent years, G. vermiculophylla has been discovered in the Long Island Sound (LIS) estuary growing alongside the native congener Gracilaria tikvahiae. The goal of this study was to determine whether the two strains of G. vermiculophylla from different regions of the world have evolved genetic differences (i.e., ecotypic differentiation) or if the physiological performance of the strains simply reflects phenotypic plasticity. Two strains of G. vermiculophylla (isolated in Korea and LIS) and a strain of the LIS native G. tikvahiae were grown for four weeks under temperatures ranging from 20 to $34^{\circ}C$ using a temperature gradient table (all other environmental conditions were kept constant). At the end of each week, wet weight of each sample was recorded, and thalli were reduced to the original stocking density of $1gL^{-1}$ (excess biomass was preserved for tissue carbon and nitrogen analysis). Generally, the growth rates of Korean G. vermiculophylla > LIS G. vermiculophylla > G. tikvahiae. After one week of growth G. tikvahiae grew 9.1, 12.0, 9.4, and 0.2% $d^{-1}$, at temperatures of 20, 24, 29, and $34^{\circ}C$, respectively, while G. vermiculophylla (LIS) grew 6.6, 6.2, 5.7, and 3.6% $d^{-1}$. G. vermiculophylla (Korea) grew 15.4, 22.9, 23.2, and 10.1% $d^{-1}$, much higher than the two strains currently inhabiting the LIS. On average, the LIS G. vermiculophylla strain contained 4-5% DW N, while the Korean strain and G. tikvahiae had more modest levels of 2-3% N DW. However, tissue N content declined as temperature increased in LIS and Korean G. vermiculophylla. The non-native haplotype may have evolved genetic differences resulting in lower growth capacity while concentrating significantly more nitrogen, giving the non-native a competitive advantage.

• Journal of Preventive Medicine and Public Health
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• 제35권4호
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• pp.282-286
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• 2002

Objectives : The level of 4-hydroxyproline (4-Hyp) in human urine was measured using high performance liquid chromatography (HPLC) with a fluorescence detector. This method is useful for medical examinations and investigating the radicals induced by physical, chemical, mental stresses. This method is superior to many published several methods in terms of its low cost and ability to analyze many samples. Methods : The urine from workers in a tire manufacturing company (22 male pre- and post-shift workers) and 18 office-workers as controls were analyzed. Data concerning age, the cumulative drinking amount and the cumulative smoking amount was collected with a questionnaire. The optimum applied amount of dansyl-Cl, the optimum reaction temperature and time, the recoveries and the optimum pH of the eluent and buffer were determined.4-Hyp from human urine was derivatized with dansyl-Cl (dimethylamino-naphthalene-1-sulfonyl chloride) after removing the a-amino acid by a treatment with phthalic dicarboxaldehyde (OPA) and cleaned with Bond Elut C18 column. The 4-Hyp derivatives were separated on a reversed phase column by gradient elution with a phosphate buffer (5 mmol, pH 8.0) and acetonitrile, and detected by fluorescence measurements at 340 nm (excitation) and 538 nm (emission). Results : The detection limit for the urinary free 4-Hyp was $0.364{\mu}mol/l$. The recovery rate of 4-Hyp was 99.7%, and the effective pH of the phosphate buffer and borate buffer were 3.0 and 8.0, respectively. From statistical analysis, age, drinking and smoking did not affect the urinary free 4-Hyp in both the controls and workers. The range of urinary 4-Hyp in the controls, pre-shift, and post-shift workers were 0.33-16.44, N.D-49.06, and $0.32-56.27{\mu}mol/l$. From the pared-sample t-test, the urinary 4-Hyp levels in post-shift workers ($11.82{\pm}6.73\;nmmol/mg\;Cre$) were 2-fold higher than in pre-shift workers ($5.36{\pm}5.53\;nmol;/mg\;Cre$) and controls ($4.91{\pm}4.89\;nmol;/mg\;Cre$). Conclusions : This method was developed with high sensitivity, accuracy, and precision. The present method was effectively applied to analyze the urinary free 4-Hyp in both controls and workers.

• 한국식품과학회지
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• 제51권5호
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• pp.420-424
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• 2019

본 연구는 해양수산물 유래 기능성 소재인 감태의 지표성분 분석법 검증 및 표준화를 위하여 HPLC를 이용하여 dieckol의 분석법을 확립하고 분석법에 대한 유효성 검증(validation)을 실시하고자 하였다. Dieckol 분석을 위하여 0.1% trifluoroacetic acid가 첨가된 water와 acetonitrile을 이동상으로 Capcell pak $C_{18}$ ($250{\times}4.6mm$, $5.0{\mu}m$) 컬럼을 사용하여 HPLC 방법을 통해 분석한 결과, 표준용액과 감태추출물의 dieckol RT이 일치하고 3.37의 높은 분리도(Rs)를 나타내었으며, UV spectrum이 일치하는 특이성을 확인하였다. 또한 검량선의 상관계수($r^2$)는 0.9994로 높은 직선성을 나타냈으며, 검출한계(LOD)와 정량한계(LOQ)는 0.38과 $1.16{\mu}g/mL$로 각각 확인되었다. 분석법의 재현성을 검증하기 위한 intra-day 및 inter-day 분석에서 RSD는 각각 1.7%와 1.00-1.25%로 나타났으며, 회수율은 99.42-101.32%이였으며 RSD는 2% 이하로 산출되어 정밀성이 있음을 확인하였다. 이상의 결과로부터 HPLC를 이용한 dieckol의 분석법은 감태추출물의 기능성원료 표준화를 위한 지표성분 분석법으로 적합함을 확인하였다. 본 시험법에 따라 분석한 감태추출물 내의 dieckol의 평균 함량은 약 0.11 g/g (10.54%)로 상대표준편차는 0.5% 이하였다. 따라서 이상의 분석결과를 통해 확립된 dieckol 분석법이 향후 감태추출물의 건강기능성식품 기능성 원료 개발과 표준화를 위한 기초자료로 크게 활용될 것으로 기대된다.

• 한국정보전자통신기술학회논문지
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• 제12권2호
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• pp.170-177
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• 2019

본 논문에서는 4족복 보행 로봇의 주행 안정성을 개선하기 위한 3가지 이론을 제시한다. 첫 번째는 Minimum-Jerk Trajectory를 이용하여 다리궤적을 최적화 시킨다. 두 번째는 본 논문에서 새롭게 제시한 사인파와 기존의 방식인 LSM을 Jerk값에 근거하여 비교한다. 셋째는 ADAMS-MATLAB co-simulation을 이용하여 반복적인 로봇 시뮬레이션을 통해 스웨이의 최적 보폭을 계산한다. 위의 과정을 통해 로봇의 보행 개선점을 기존의 이론과 비교하여 나타내었다. 첫 번째로 정 보행시 몸체와 타원형태의 다리 끝의 움직임에 Minimum-Jerk trajectory를 사용하여 다리궤적이 급격하게 변하는 지점의 평균 기울기를 최소 1.2에서 최대 2.9까지 감소시켜 지면에 다리 끝점이 도달할 때 충격을 최소화하여 안정성을 증가 하였다. 두 번째로 기존 LSM(Longitudinal Stability Margin)기법과 본 논문에서 제시한 사인파형 Sway를 사용하여 비교한 결과 평균 Jerk를 Z축에서 0.019, X축에서 0.457, Y축에서 0.02, 3D는 0.479 만큼 감소 시켰다. 특히 X축 Jerk는 크게 감소 하였다. 셋째로 로봇이 최소 Jerk 값으로 보행하기 위한 최적의 보폭의 길이를 상기 분석을 통해 도출하였으며 그 결과 20cm보폭 길이가 가장 안정적이었다.

• 공업화학
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• 제29권6호
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• pp.759-764
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• 2018

내재적 미세 다공성 고분자(polymer of intrinsic microporosity, PIM-1)를 사용하여 빈용매 유도 상전이법으로부터 3차원 다공성 구조를 가지는 필름을 형성하고, 이를 탄화하여 3차원 다공성 탄소(cNPIM)를 제조하였다. 전자주사현미경 분석을 통해 상전이 공정을 적용한 탄소소재가 마이크로, 메조, 매크로 기공을 모두 가지면서 서로 연결된 계층적 3차원 다공구조를 나타냄을 확인하였다. 특히 상전이 공정의 용매의 함량비를 조절함으로써 기공구조를 제어할 수 있었으며, 결과적으로 평균 0.75 nm의 기공 크기와 $2101.1m^2/g$의 높은 비표면적을 가지면서 약 30%의 메조, 마크로 기공구조를 겸비한 최적화된 다공성 탄소 전극을 제조할 수 있었다. 제조된 3차원 다공성 탄소소재를 전기이중층 캐퍼시터용 전극물질로 사용하여 수계전해질에서 측정한 결과, 높은 비표면적을 가지는 탄소 소재 내의 비약적 이온 이동속도 향상 효과로 높은 비축전용량(304.8 F/g@10 mV/s)과 우수한 충 방전 속도(77% 용량유지율@100 mV/s)를 나타내었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.