Brucella abortus is a well-known intracellular zoonotic pathogen. Despite significant research to understand the pathogenesis, underlying mechanisms of the bacterial infection are not yet understood. Thus, prevention and control of the B. abortus infection is problematic in animal and human. Therefore, several methods involving random mutation have been used to identify the mechanisms and provide a solution for control and prevention of Brucella infection. B. abortus mutants were generated by random insertion of a transposon, Ez-Tn5TM pMODTM-3 <R6Kγori/MCS> into a chromosome. Characteristics of these mutants were investigated using biochemical testing, growth features, determination of biovar, antibiotic resistance and detection of virulence factors, T4SS, PGK, and CGS. In biochemical testing, B. abortus mutants were categorized according to 7 groups with different condition of ILATk, SUTC, and ELLM. Different growth features were also observed between wild type and mutants. In addition, both B. abortus wild type and mutants were determined as biovar type 1 by biovar test. Three virulence factors, T4SS, PGK, and CGS were detected by PCR. Therefore, B. abortus mutants were characterized by analysis of phenotyping and it might be useful for further studies of known pathogenesis of B. abortus infection and for identification of diagnostic markers of brucellosis.

A steady-state controllable M/G/1 queueing model operating under the (TN) policy is considered where the (TN) policy is defined as the next busy period will be initiated either after T time units elapsed from the end of the previous busy period if at least one customer arrives at the system during that time period, or the time instant when Nth customer arrives at the system after T time units elapsed without customers’ arrivals during that time period. After deriving the necessary system characteristics such as the expected number of customers in the system, the expected length of busy period and so on, the total expected cost function per unit time in the system operation is constructed to determine the optimal operating policy. To do so, the cost elements associated with such system characteristics including the customers’ waiting cost in the system and the server’s removal and activating cost are defined. Then, the optimal values of the decision variables included in the operating policies are determined by minimizing the total expected cost function per unit time to operate the system under consideration.

본 연구는 식물성 플랑크톤의 1차 생산력에 대한 N:P ratio의 영향을 분석하기 위해 “영양염 첨가실험(NEBs)”을 실시하였다. 영양염 첨가실험(NEBs)에 의한 N:P Ratio의 영향은 대청호에서 측정된 수질데이터와 비교분석하였다. 단기 영양염 첨가실험 결과, 인 (P)을 첨가한 처리군들 (N:P Ratio=5, 15, 20, 30)에서의 1차 생산력의 반응이 대조군 (Control)과 인(P)을 첨가한 처리군 (N:P Ratio=80, TV), 질소(N)를 첨가한 처리군(N:P Ratio=150, TVI)에서보다 높았다. 또한 질소 (N)를 처리한 처리군에서는 대조군과 모든 처리군에서보다 1차 생산력의 반응이 유의하게 작았다. 영양염 첨가실험의 결과, 식물성 플랑크톤의 성장에 인이 제한영양염으로 작용하고 있었으며, 질소첨가 (Spiking N)는 식물성 플랑크톤의 성장을 억제한 것으로 사료된다. 대청호의 영양염 변이 분석 결과, 최소 N:P Ratio에서 엽록소-a의 최대농도가 나타났고, N:P Ratio는 식물성 플랑크톤의 성장에 대한 핵심 조절자로 사료되었다. 본 연구결과를 종합해 볼 때, N:P Ratio가 식물성 플랑크톤의 성장을 조절하는 핵심 인자로 작용 할 것으로 사료된다.