For the purposes of this paper, stress may be defined as any modification of environmental parameters that leads to a response by biological organisms. Stresses that affect biological structures may be non-thermal, such as ultraviolet radiation, pH, or salinity, or thermal. Temperature is one of the major stresses that all living organism face. The major effects of cold shock are decrease of membrane fluidity and the stabilization of secondary structures of RNA and DNA in the cells, which may effect the efficiency of translation, transcription, and DNA replication. In this study in compliance with the cold temperature stress about selection of the useful gene is contents from the silkworm which is been revealed. The survival rate which is caused by with the cold temperature stress until 12 hours was 100% in 0℃, until 2 hours was 100% in -5℃. A total of 960 clones were randomly selected from the subtraction cDNA library, and then performed a differential display hybridization analysis with forward and reverse probes. In conclusion, selected 53 partial clones and novel 2 full-length clones were identified as differential expressed genes. We assumed that the novel gene related with transmembrane.

이 연구는 뇌동맥자루의 임상적 진단에 사용되는 3차원 디지털 혈관조영술과 3차원 디지털 감산 혈관조 영술을 동일 부위에 시행한 환자 53명의 영상에서 뇌동맥자루 경부 직경, 최대 직경, 최대 면적 및 체적을 측정하고, 각 검사법의 영상 노이즈와 피폭선량을 분석하여 뇌동맥자루 진단검사에서의 임상적 진단 차이를 비교하였다. 3차원 디지털 혈관조영술과 3차원 디지털 감산 혈관조영술에서 뇌동맥자루의 경부직경, 최대 직경, 최대면적, 체적, 노이즈를 비교한 결과가 일치하거나 아주 미세한 차이로 나타났다. 하지만, 방사선 피폭선량은 3차원 디지털 감산 혈관조영술에 비하여 3차원 디지털 혈관조영술이 현저히 낮게 발생하였다. 따라서 뇌동맥자루의 임상적 진단을 목적으로 시행하는 경우에는 환자의 피폭선량을 감소를 위해 3차원 디지털 혈관조영술이 우선적으로 사용되어야 할 것이다.

Column subtraction, originally proposed by Harche and Thompson(1994), is an exact method for solving large set covering, packing and partitioning problems. Since the constraint set of ship scheduling problem(SSP) have a special structure, most instances of SSP can be solved by LP relaxation This paper aim, at applying the column subtraction method to solve SSP which am not be solved by LP relaxation For remained instances of unsolvable ones, we subtract columns from the finale simplex table to get another integer solution in an iterative manner. Computational results having up to 10,000 0-1 variables show better performance of the column subtraction method solving the remained instances of SSP than complex branch and-bound algorithm by LINDO.