A 12-year-old intact female Schnauzer was referred for the evaluation of poorly controlled diabetes mellitus: despite insulin therapy, blood glucose concentration was consistently high, indicating a decreased insulin sensitivity. Laboratory analyses revealed persistent hyperglycemia, glucosuria, and ketonuria. Diagnostic approaches were performed to identify concurrent disorders that can cause insulin resistance. The dog was found to have concurrent hyperadrenocorticism, hyperlipidemia, pancreatitis, and vaginal cytology indicating diestrus in the estrus cycle. Trilostane administration for hyperadrenocorticism improved the insulin response; however, the dog remained hyperglycemic. Eventually, the dog showed complete remission without insulin administration 1 week after the ovariohysterectomy. The dog remained in remission for approximately 4 months, but eventually relapsed and the condition was permanent. Diestrus in intact females and hyperadrenocorticism are known to be the two main causes of insulin resistance in dogs. After the management of these conditions, the dog achieved diabetes remission, which rarely achieves in dogs. In cases of insulin resistance, such as hormonal imbalances or inflammatory conditions, remission can be achieved by addressing the underlying cause. Hence, it is important to assess the presence of comorbidities associated with insulin resistance in dogs with poorly controlled diabetes mellitus and to treat each condition as soon as possible.

세계적 선박 배출가스 저감에 대한 규제로 인해 항만 및 부두에서 육상전원공급장치(AMP, Alternative Marine Power)가 지속 적으로 사용되고 있다. 국내 또한 항만 대기질 개선 특별법에 따라 AMP의 사용이 의무화되고 있고, 다양한 친환경선박과 연계하여 활 용하도록 지속적인 시도를 하고 있다. 본 논문에서는 AMP를 통해 선내 전력을 공급하는 상황을 모델링 하여 AC Load Flow Analysis를 수행하였다. 이를 통해 선박에 전력이 공급될 때의 전기적 파라미터와 손실 등에 대해서 분석할 수 있다. 아울러 Transient Stability Analysis를 통해 계통의 사고 발생 시 선내 발전기를 통한 무정전전환에 대한 HSGT(High Speed Generation Transfer)의 한계값을 도출하고 이를 적용하였을 경우 결과에 대해 검토하였다.

Corrosion of copper (Cu) canisters is one of the important factors to ensure the safety of a deep geological repository site. This is because the corrosion of a canister may induce failure of the canister which can lead to a release of radionuclides into the environment. Corrosion of canisters for highlevel wastes is affected by the following multiphysics: thermal-hydraulics, transportation of chemical species, chemical reactions, and interface reactions. This research aimed to develop a multiphysics numerical model for the corrosion of spent nuclear fuel canisters for a deep geological repository in South Korea. The multiphysics model is based on MOOSE (Multiphysics Object-Oriented Simulation Environment) which uses a finite element method. In the multiphysics model, the following multiphysics are coupled and solved together for a deep geological repository design of South Korea: interface redox reactions, porous flow, and heat transport in porous flow. The proposed model was validated with experimental data before being applied to a KAERI reference disposal unit. It was found that the corrosion potential of a Cu canister shows an uneven distribution of corrosion potential along with the surface. In addition, top, bottom, and side surfaces of the canisters show a different lifetime and corrosion potential. Important redox reactions for corrosion are changed along with time from a reduction of O2 and anodic dissolution of Cu by Cl− to sulfidation of Cu and reduction of water. The proposed model will be coupled with some important chemical reactions in engineering buffers and will be the base for the understanding of the behavior of Cu canisters in the KAERI reference disposal unit.

알코올의 탈수를 위하여 에너지 다소비 공정인 증류 공정을 투과증발 막 공정으로 대체하려는 연구가 많이 진행 되어져 왔다. 대표적인 투과증발 막인 PDMS 분리막에 대한 시간의존적 분리 거동은 분리 메카니즘의 이해에 매우 중요하다. 따라서 본 연구에서는 50 wt% 에탄올-물 혼합용액에 대하여 50°C에서 막면적 1194 cm2인 PDMS/PSF 분리막 모듈의 시간의 존적인 투과증발 분리 거동을 고찰하였다. 총 유속과 에탄올/물 분리계수는 투과증발 시간이 증가함에 따라서 초기에 증가하 다가 다시 감소하였다. 초기 분리성능의 증가는 건조한 PDMS 분리막에 에탄올이 용해되는데 시간이 걸리기 때문이며, 후기 분리성능의 감소는 주입 탱크의 에탄올 농도가 시간에 따라서 감소하기 때문에 나타나는 현상이었다. 따라서 본 연구로부터 PDMS 분리막을 통한 에탄올의 투과는 용해-확산 메카니즘에 의해 발생된다는 것이 재확인되었다.

Activation of transient receptor potential vanilloid 1 (TRPV1), a calcium permeable channel expressed in primary sensory neurons, induces the release of glutamate from their central and peripheral afferents during normal acute and pathological pain. However, little information is available regarding the glutamate release mechanism associated with TRPV1 activation in primary sensory neurons. To address this issue, we investigated the expression of vesicular glutamate transporter (VGLUT) in TRPV1-immunopositive (+) neurons in the rat trigeminal ganglion (TG) under normal and complete Freund’s adjuvant (CFA)-induced inflammatory pain conditions using behavioral testing as well as double immunofluorescence staining with antisera against TRPV1 and VGLUT1 or VGLUT2. TRPV1 was primarily expressed in small and medium-sized TG neurons. TRPV1+ neurons constituted approximately 27% of all TG neurons. Among all TRPV1+ neurons, the proportion of TRPV1+ neurons coexpressing VGLUT1 (VGLUT1+/ TRPV1+ neurons) and VGLUT2 (VGLUT2+/TRPV1+ neurons) was 0.4% ± 0.2% and 22.4% ± 2.8%, respectively. The proportion of TRPV1+ and VGLUT2+ neurons was higher in the CFA group than in the control group (TRPV1+ neurons: 31.5% ± 2.5% vs. 26.5% ± 1.2%, VGLUT2+ neurons: 31.8% ± 1.1% vs. 24.6% ± 1.5%, p < 0.05), whereas the proportion of VGLUT1+, VGLUT1+/TRPV1+, and VGLUT2+/TRPV1+ neurons did not differ significantly between the CFA and control groups. These findings together suggest that VGLUT2, a major isoform of VGLUTs, is involved in TRPV1 activation-associated glutamate release during normal acute and inflammatory pain.

다중 하중 과도응답해석은 시간에 따른 작용 하중에 대한 과도응답을 확인하므로 정교한 시스템 모델링 및 조밀한 시간 간격을 가 질수록 해당 시스템에 대한 동특성은 정확하게 나타내지만 이에 따른 계산 시간은 크게 증가하게 된다. 크리로프 부공간 기반 모델차 수축소법은 기계 시스템이 가지는 동적 특성과 거의 동일한 결과를 나타내면서 계산 시간을 줄일 수 있기 때문에 효율적인 과도응답 해석 방법이다. 본 연구에서는 다중 하중 및 이동 하중을 가지는 수치 예제를 통하여 크리로프 부공간 모델차수축소법 기반 과도응답 해석을 수행하고, 이를 통해 초기 시스템 및 축소차수 모델의 정확성 및 효율성을 비교하였다. 또한, 시스템 행렬 추출, 크리로프 부공 간의 기저 벡터로 구성되는 변환행렬 생성 및 축소차수모델 생성 그리고 이를 바탕으로 과도응답해석을 하는 절차를 수립하여 상용 유한요소 프로그램인 ANSYS Workbench ACT를 통해 과도응답해석 과정 자동화를 구현하여 그 효용성과 효율성을 보였다.

The temperature distributions were numerically calculated for the two-dimensional transient conduction heat transfer problem of a square plate. The obtained temperature distributions were converted into colors to create images, and they were provided as learning and test data of CNN. Classification and regression networks were constructed to predict representative wall temperatures through CNN analysis. As results, the classification networks predicted the representative wall temperatures with an accuracy of 99.91% by erroneously predicting only 1 out of 1100 images. The regression networks predicted the representative wall temperatures within errors of C. From this fact, it was confirmed that the deep learning techniques are applicable to the transient conduction heat transfer problems.