The effects of earthquake experience on disaster education for children and teens

The purpose of this study is to examine the factors of disaster experience that impact the effectiveness of disaster education on school students (children and teens). Following the magnitude 5.4 Pohang earthquake in 2017, Pohang City Hall conducted a school earthquake disaster education program over a period of four months (August to November) in 2018. Professors and graduate students from the Ulsan National Institute of Science and Technology taught around 5000 middle and high school students, while also conducting surveys. The experiences of the Pohang earthquake were analyzed and divided into cognitive responses and emotional responses. Students who felt activated emotional responses, surprise and fear, but not joy, tended to have more effective educational experiences. On the other hand, unpleasant emotional reactions, such as anger and sadness, had a negative effect on educational effectiveness. The cognitive response, which is perceived intensity in this research, did not impact educational effectiveness significantly. These results imply that the emotional responses of students are more important than their cognitive responses in providing a disaster education program. This means that even though an earthquake may be small in magnitude and may not cause physical damage, we still need to provide immediate disaster education to the children and teens if they are surprised and afraid of future disasters

Delayed Diagnosis of an Intraurethral Foreign Body Causing Urosepsis and Penile Necrosis

Cases of self-inserted foreign bodies in the male urethra and urinary bladder are unusual. In most cases, the type of foreign body can be identified by taking a history or from radiological findings; sometimes, however, it is difficult to identify the foreign body because of decreased mental capacity of the patient or unknown radiological characteristics of the foreign body. We experienced a chronic alcoholic patient with septicemia and penile necrosis in whom a fragment of mirror glass had passed through the urethra into the bladder. The glass, 2 cm in length and 0.7 cm in diameter, was detected by cystoscopy and was removed by using a resectosope

Rapid Hepatobiliary Excretion of Micelle-Encapsulated/Radiolabeled Upconverting Nanoparticles as an Integrated Form

In the field of nanomedicine, long term accumulation of nanoparticles (NPs) in the mononuclear phagocyte system (MPS) such as liver is the major hurdle in clinical translation. On the other hand, NPs could be excreted via hepatobiliary excretion pathway without overt tissue toxicity. Therefore, it is critical to develop NPs that show favorable excretion property. Herein, we demonstrated that micelle encapsulated Cu-64-labeled upconverting nanoparticles (micelle encapsulated Cu-64-NOTA-UCNPs) showed substantial hepatobiliary excretion by in vivo positron emission tomography (PET) and also upconversion luminescence imaging (ULI). Ex vivo biodistribution study reinforced the imaging results by showing clearance of 84% of initial hepatic uptake in 72 hours. Hepatobiliary excretion of the UCNPs was also verified by transmission electron microscopy (TEM) examination. Micelle encapsulated Cu-64-NOTA-UCNPs could be an optimal bimodal imaging agent owing to quantifiability of Cu-64, ability of in vivo/ex vivo ULI and good hepatobiliary excretion property.

Social Construction of the ESS Fires in Korea: Focusing on Social Context Changes and the Stakeholders??? Experiences

Department of Urban and Environmental Engineering (Disaster Management Engineering)ope

Social construction of fire accidents in battery energy storage systems in Korea

Renewable energy (RE) has the potential to become an essential part of the national policy for energy transition. The government of the Republic of Korea has sought to solve the problem of RE intermittency and achieve flexible grid management by leveraging a powerful policy drive for battery energy storage system (B-ESS) technology. However, from 2017 to 2019, over two dozen B-ESS fire accidents occurred across Korea. Consecutive fires in B-ESSs, which were expected to be game-changers in energy transition, have instead become an issue of social concern. This study aims to analyze the influence of various social factors on fire accidents, for which previous studies could not provide sufficient explanation. A literature analysis and qualitative interviews revealed the social construction process of B-ESS fires through stakeholder interaction. The economic incentive schemes of B-ESS and insufficient safety regulations has had a significant influence on the interactions of relevant social groups (RSGs), and several factors in the environment, organizations, and cognition/choice of RSGs have exacerbated fire risks. This research provides a clearer understanding of the adverse outcomes of adopting new energy technologies

Governmental Disaster Assistance and Moral Hazard: Focusing on the Slight Damage Assistance Program for the Pohang Earthquake Victims

This study shows that an inappropriately designed disaster assistance program may provoke disaster victims to commit fraud, resulting in moral hazard. We analyzed the case of the Pohang earthquake in 2017 using three data sources: stakeholder interviews, newspaper articles, and posts on online community boards. Although its magnitude was not catastrophic (M 5.4), the earthquake had a significant impact on local residents who were not familiar with managing earthquakes. The Korean government distributed individual disaster assistance grants. However, the lack of a monitoring process resulted in negative consequences to some earthquake victims who received the slight damage assistance grants. These negative results imply a moral hazard from the principal-agent perspective. We examined whether the slight damage assistance program in Korea should be maintained, despite its negative consequences

Semantic Scene Graph Generation Using RDF Model and Deep Learning

Over the last several years, in parallel with the general global advancement in mobile technology and a rise in social media network content consumption, multimedia content production and reproduction has increased exponentially. Therefore, enabled by the rapid recent advancements in deep learning technology, research on scene graph generation is being actively conducted to more efficiently search for and classify images desired by users within a large amount of content. This approach lets users accurately find images they are searching for by expressing meaningful information on image content as nodes and edges of a graph. In this study, we propose a scene graph generation method based on using the Resource Description Framework (RDF) model to clarify semantic relations. Furthermore, we also use convolutional neural network (CNN) and recurrent neural network (RNN) deep learning models to generate a scene graph expressed in a controlled vocabulary of the RDF model to understand the relations between image object tags. Finally, we experimentally demonstrate through testing that our proposed technique can express semantic content more effectively than existing approaches