Translational control is a strategy for various viruses to manipulate their hosts to suppress any acute antiviral activity. Some cys-motif genes encoded in polydnaviruses or teratocytes act as host translation inhibitory factor (HTIF) to defend the host antiviral activity. A novel cys-motif gene, TSP13, was encoded in the genome of an endoparasitoid wasp, Cotesia plutellae. TSP13 consists of 129 amino acid residues with a predicted molecular weight of 13.987 kDa and pI value at 7.928. Genomic DNA region encoding open reading frame is interrupted with three introns. TSP13 was expressed in Plutella xylostella larvae parasitized by C. plutellae. C. plutellae bracovirus (CpBV) was purified and injected to nonparasitized P. xylostella. In the virus-injected P. xylostella, TSP13 was shown to be expressed by RT-PCR analysis. Thus, TSP13 was turned out to be encoded in the proviral CpBV genome. TSP13 was cloned into a eukaryotic expression vector, which was then used to infect Sf9 cells to transiently express TSP13. The synthesized TSP13 was detected in the culture broth. Purified TSP13 significantly inhibited cellular immune responses. Furthermore, TSP13 entered the target cells and was localized in the cytosol. This study reports a novel cys-motif gene, which is encoded in CpBV genome localized on chromosome(s) of C. plutellae and replicated to be encapsidated in the episomal viral particles during parasitization.

현재 TSP(Touch Screen Panel)는 스마트폰을 비롯한 태블렛 PC, 대형 광고용 TSP 등으로 점점 대형화되고 있다. 화면이 점점 대면적화되면 기존 ITO(Indium Tin Oxide)전극을 센서 전극으로 사용하면 응답 속도가 늦어지는 문제점이 발생하게 된다. 이러한 문제점을 해결하기 위해서 센서 전극을 ITO대신에 nano silver paste를 이용하는 기술이 개발되고 있다. 본 연구에서는 새로운 합성법인 전자빔으로 nano silver powder를 개발하였다. 이렇게 개발된 nano silver powder와 이미 개발된 submicron silver powder를 혼합하여 hybrid silver paste를 제조하였다. 제조된 paste를 이용하여 4㎛, 7㎛의 미세패턴을 구현할 수 있었다.

본 연구에서는 베젤 전극의 최소화 방안으로서 감광성 실버 페이스트법을 적용하여 전도성 패턴을 구현하였다. 이러한 감광성 실버 페이스트를 이용하여 패턴을 구현하는데 가장 중요한 공정은 예비건조(pre-heating) 공정과 UV노광(UV-exposure)공정이다. 따라서 본 연구에서는 이러한 2가지 핵심공정에 대해서 연구한 결과, 예비건조 온도는 90℃ 10분, UV노광량은 300mJ/㎠이 최적 조건임을 알 수 있었다. 이와같은 조건으로 20/20㎛(Line/Space)패턴까지 구현할 수 있었다.

서울시에서 설치하여 운영중인 대기질 측정소의 입자상물질을 대표하는 PM2.5, PM10, TSP와 황사기간 중 고용량고기포집기로 채취한 먼지성분을 분석, 평가하였다. 1990년도부터 2002년 11월까지 서울에서 관측된 황사일수는 2000년 이후 발생빈도가 증가하였으며 황사지속시간도 길어지는 경향을 보였다. PM10/TSP 비율은 황사시 2000년, 2001년도에 각각 52.9%, 59.4%로 비황사시에 비해 PM10의 비율이 약 10% 정도 낮은 것으로 미루어 황사시 10 μm이상의 입경이 큰 입자 영향이 컸던 반면에 2002년 황사시에는 PM10의 영향이 오히려 크게 나타나 PM10이 TSP 중의 71.4%에 달하였다. 황사가 전체 먼지농도에 미치는 기여율은 2002년도에 PM2.5 11.9%, PM10 23.1%, TSP 19%로 가장 높은 기여도를 보여 황사가 전체 면지농도에 미치는 영향이 매우 크다는 것을 알 수 있었다.

Parallel Genetic Algorithms partition the whole population into several sub-populations and search the optimal solution by exchanging the information each others periodically. Distributed Genetic Algorithm, one of Parallel Genetic Algorithms, divides a large population into several sub-populations and executes the traditional Genetic Algorithm on each sub-population independently. And periodically promising individuals selected from sub-populations are migrated by following the migration interval and migration rate to different sub-populations. In this paper, for the Travelling Salesman Problems, we analyze and compare with Distributed Genetic Algorithms using different Genetic Algorithms and using same Genetic Algorithms on each separated sub-population The simulation result shows that using different Genetic Algorithms obtains better results than using same Genetic Algorithms in Distributed Genetic Algorithms. This results look like the property of rapidly searching the approximated optima and keeping the variety of solution make interaction in different Genetic Algorithms.

For a long time, genetic algorithms have been recognized as a new method to solve difficult and complex problems and the performance of genetic algorithms depends on genetic operators, especially crossover operator. Various problems like the traveling salesman problem, the transportation problem or the job shop problem, in logistics engineering can be modeled as a sequencing problem This paper proposes modified genetic crossover operators to be used at various sequencing problems and uses the traveling salesman problem to be applied to a real world problem like the delivery problem and the vehicle routing problem as a benchmark problem Because the proposed operators use parental information as well as network information, they could show better efficiency in performance and computation time than conventional operators.

Our interest in this paper is in the efficient computation of a good low bound for the traveling salesman problem and is in the application of a network problem in agriculture. We base our approach on a relatively new formulation of the TSP as a two-commodity network flow problem. By assigning Lagrangian multipliers to certain constraints and relaxing them, the problem separates into two single-commodity network flow problems and an assignment problem, for which efficient algorithms are available.