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      • KCI등재

        The Impact of the Russo-Ukraine War on the EAEU’s Political and Economic Integration

        신은지,이재승 고려대학교 일민국제관계연구원 2023 국제관계연구 Vol.28 No.2

        This study examines the far-reaching impact of the Russian invasion of Ukraine in 2022 on the Eurasian Economic Union (EAEU) in terms of political and economic integration. The EAEU, formed in 2015, aimed for deep integration among member states with a focus on sustainable economic development and a common market. However, the actual implementation of these objectives has faced challenges, and external shocks such as the war in Ukraine have raised questions about the union’s ability to balance geopolitical complexities and internal political cohesion for economic growth. The conflict has revealed divisions among EAEU member states, particularly on the dissonance among member states over its stance towards the Russo-Ukrainian war. While economic concerns largely influenced the responses of Kazakhstan and Kyrgyzstan, security dependencies primarily motivated Belarus and Armenia. Nevertheless, the EAEU has demonstrated economic resilience, with member states like Armenia, Kyrgyzstan, and Kazakhstan experiencing economic growth,driven by their roles as logistical hubs and beneficiaries from positive trade flows. The study suggests that the outcome of the Russo-Ukraine war will significantly shape the EAEU’s future, with a victorious Russia potentially deepening political integration, while a less favorable outcome could exacerbate the existing political divisions. The EAEU’s path forward involves reconciling internal political differences while leveraging its economic strengths, as it stands at a critical crossroad, facing both political challenges and economic opportunities that could enhance its global relevance. This study contributes to the understanding of how geopolitical crises affect regional integration and sets the stage for future research on the EAEU’s evolving dynamics in a complex international context.

      • 위험물 안전관리·관계자 전계층의 역량 및 환경에 관한 Data Analytics 분석

        신은지,박소현,신동일 한국화재감식학회 2020 한국화재감식학회 학회지 Vol.11 No.4

        Increased use of hazardous materials increases overall number of safety accidents such as leaks, fires, and explosions. Also, it causes environmental damage such as water pollution and air pollution, exacerbating extensive and diverse damage. In this study, a wide range of surveys were conducted on the entire groups related to safety management of hazardous materials, including safety managers and carriers responsible for safety management at hazardous materials industrial sites, and safety management agents and tank performance test workers who are specialized of hazardous materials, and civil service personnel and inspectors at fire stations. Because the sample size was large for each group, a multi-faceted survey was analyzed using data analytics such as correlation analysis and regression. The results show the findings in the aspect of safety capabilities and institutional environment to be improved for the enhanced safety management of hazardous materials.

      • KCI등재

        Ceriporia lacerata 균사체 배양물의 혈당 강하 활성 평가

        신은지,김지은,김지혜,박용만,윤성균,장병철,이삼빈,김병천 한국식품저장유통학회 2015 한국식품저장유통학회지 Vol.22 No.1

        To investigate the hypoglycemic effect of the submerged culture of the Ceriporia lacerata mycelium (CL01) species, in-vitro and in-vivo tests were executed using INS-1 and 3T3-L1 cells, normal and diabetic mice. CL01 exhibited an inhibitory effect on cell death through dexamethasone in the INS-1 cells, and increased the GLUT4 expression in the 3T3-L1 cells. A hematological monitoring test was executed using diabetic mice divided into four groups : normal control (G1), negative control (G2), positive control (G3), and CL01 250 mg/kg (G4) groups, which were fed daily for 6 weeks. The body weight gain, food intake, and water intake of G4 were not significantly different from those of G2. After 5 weeks, the blood glucose levels of G4 were significantly different from those of G2. After 6 weeks, the plasma insulin levels of G4 increased by about 36% compared to those of G2, and the plasma C-peptide levels of G4 were lower by about 18%. than those of G3. The results of the oral glucose tolerance test (OGTT) showed that CL01 lessened the blood glucose levels of G4 by 15% compared to G2. It was concluded that CL01 stimulates the proliferation of beta cells and promotes insulin secretion and may thus have a potential in improving the hypoglycemic effects among the diabetic symptoms.

      • KCI등재

        db/db 마우스에서 Ceriporia lacerata 균사체 배양액이 GLUT4 발현에 미치는 영향

        신은지,김지은,김지혜,박용만,윤성균,장병철,이삼빈,김병천 한국식품저장유통학회 2015 한국식품저장유통학회지 Vol.22 No.6

        In this study, we evaluated the antidiabetic effect of a submerged culture of Ceriporia lacerata mycelium (CL01) on hematological indices, as well as protein and mRNA expression of the insulin-signaling pathway, in db/db mice. After CL01 was administrated for 4 weeks, blood glucose levels decreased consistently, and plasma insulin and c-peptide levels each decreased by roughly 55.8%, 40% of those in the negative control (p<0.05). With regard to HOMA-IR, an insulin resistance index, insulin resistance of the CL01-fed group improved over that of the negative control group by about 62% (p<0.05). In addition, we demonstrated that the protein expression levels of pIR, pAkt, pAMPK, and GLUT4 and the mRNA expression levels of Akt2, IRS1, and GLUT4 in the muscle cells of db/db mice increased in the CL01-fed group compared to the corresponding levels in the control group. These results demonstrate that CL01 affects glucose metabolism, upregulates protein and gene expression in the insulin-signaling pathway, and decreases blood glucose levels effectively by improving insulin sensitivity. More than 90% of those who suffer from type 2 diabetes are more likely to suffer from hyperinsulinemia, hypertension, obesity, and other comorbidities because of insulin resistance. Therefore, it is possible that CL01 intake could be used as a fundamental treatment for type 2 diabetes by lowering insulin resistance, and these results may prove be useful as basic evidence for further research into the mechanisms of a cure for type 2 diabetes.

      • KCI등재

        무쾌감성 우울 및 정서자극에 대한 접근-회피 동기의 관계

        신은지,허효선,권석만 한국임상심리학회 2022 한국심리학회지: 임상심리 연구와 실제 Vol.8 No.2

        본 연구의 목적은 무쾌감증이 우울 장애를 불안 장애로부터 구분짓는 핵심적인 특성임을 규명하는 것이며, 실험 연구를 통해 무쾌감증과 정서 자극에 대한 접근-회피 동기의 관계를 검증하고자 했다. 이를 위해 한국판 불안-우울-고통 척도의 점수를 기준으로 무쾌감성 우울 집단(n=17)과 불안 집단(n=16) 및 통제 집단(n=19)을 모집하여 접근-회피 과제(Approach-Avoidance Task; AAT)를 실시했으며, 정서 자극의 정서가 및 각성가에 따른 개인의 접근-회피 경향성을 측정했다. 통계 분석 결과, 무쾌감성 우울 집단은 불안 집단 및 통제 집단에 비해 긍정 정서 자극에 대한 접근 동기가 유의미하게 감소되어 있었다. 또한 긍정 정서 자극의 각성가 변화에 따른 접근-회피 동기의 변화에 있어 무쾌감성 우울 집단은 불안 및 통제집단보다 덜 민감한 반응을 보였다. 본 연구의 결과는 긍정적 정서에 대한 접근 동기의 감소, 즉 무쾌감증이 우울 장애를 구성하는 핵심적인 특성임을 시사하며, AAT 과제를 통해 보다 암묵적인 접근-회피 동기를 수정 및 훈련할 수 있도록 개입에 대한 기초를 제공한다.

      • KCI등재

        Data Analytics를 활용한 위험물 화재사고 분석

        신은지,고문수,신동일 한국가스학회 2020 한국가스학회지 Vol.24 No.5

        Hazardous materials accidents are not limited to the leakage of the material, butif the early response is not appropriate, it can lead to a fire or an explosion, which increasesthe scale of the damage. However, as the 4th industrial revolution and the rise of the big dataera are being discussed, systematic analysis of hazardous materials accidents based on newtechniques has not been attempted, but simple statistics are being collected. In this study, weperform the systematic analysis, using machine learning, on the fire accident data for the past11 years (2008 ~ 2018), accumulated by the National Fire Service. The analysis results are vi sualized and presented through text mining analysis, and the possibility of developing a dam age-scale prediction model is explored by applying the regression analysis method, using themain factors present in the hazardous materials fire accident data. 위험물 사고는 해당 물질의 누출에 그치지 않고, 초기대응이 부적합한 경우, 화재, 폭발로 이어져 그 피해규모가확대될 위험이 크다. 하지만 4차 산업혁명과 빅데이터 시대의 대두가 논의되고 있는 시점에서, 새로운 기법들에 바탕한 위험물 사고의 체계적인 분석은 시도되지 못하고, 단편적인 통계 수집에 그치고 있는 것이 아쉬운 실정이다. 본 연구에서는 지난 11년간(2008~2018) 축적된 소방청 위험물 화재사고 데이터를 대상으로 기계학습에 기반한 분석을 진행하였다. Text mining 분석을 통해 분석한 자료를 시각화하여 나타내었고, 아울러 위험물 화재사고 데이터에 존재하는 주요 인자를 이용해 피해규모 예측모델의 개발 가능성을 회귀분석 방법을 적용하여 탐색하였다.

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