본 연구는 지난 10여년간 고려대학교 및 한국과학기술연구원(KIST)에서 AMS를 이용하여 측정된 우주선유발 동위원소 10 Be의 준비 및 측정 과정을 다룬 보고서이다. 총 2 4세트의 표준물질과 107개의 Blank시료가 분석되었으며, 2017년 이후 표준물질의 측정 재현성이 크게 향상되어 국제적인 주요 실험실의 결과와 비교할 만한 수준의 성과를 보였다. 그러나 Blank 값은 사용된 9 Be 캐리어의 종류 및 석영 추출 과정과 AMS 측정 세팅 등 실험 조건에 따라 영향 을 받는 것으로 나타났으며, 이는 잠재적인 오염원을 체계적으로 추적하고 관리할 필요성을 시사한다. 본 연구는 10 Be Background 값을 줄이는 것이 우주선유발 동위원소 연구의 범위를 넓히는 데 중요한 역할을 함을 강조한다. 낮은 Background 값은 상대적으로 최근에 형성된 지형이나 오랜 시간 매몰되어 방사성 핵종이 상당량 감소한, 저준위 10 Be 지형의 연대측정을 가능하게 한다. 향후 연구에서는 실험 과정을 개선하고 가중평균 계산법 등의 새로운 통계적 방법을 도입하여 측정 오차를 최소화하는 데 중점을 둘 예정이다. 본 연구는 다양한 시간적 및 공간적 규모에서 지구표면과학 연구를 발전시키기 위한 우주선유발 동위원소 분석의 기반을 제공한다.

PURPOSES : The objective of this study was to review roadway management strategies that can be utilized in the event of a radiological emergency, select feasible alternatives, and simulate a portion of the West Coast network to analyze the effectiveness of these strategies. METHODS : The methodology of the study involved reviewing the relevant literature, extracting the implications, establishing an analysis procedure, and selecting an effectiveness evaluation scale. Using a national transportation database, a network was constructed using Toba, a macroscopic model. RESULTS : A reverse-flow lane system was applied to the West Coast Expressway Glory IC–Hampyeong IC (total 25 km), and a plan to increase the number of lanes was applied to the Seokgyo Street–Shinpyeong Intersection on National Route 23 (total extension 28 km). Consequently, both road management strategies were found to be effective. CONCLUSIONS : This study examined roadway management strategies that can be utilized in the event of a radiological emergency, selected feasible alternatives, and simulated a portion of the West Coast network to verify the effectiveness of these strategies. In the case of reverse flow lanes, it is most effective when applied to expressways that can restrict the entrance and exit of vehicles. In the case of increasing the number of lanes, it is most effective when applied to general roads, and institutional arrangements should be made to enable two-way traffic to use the reserved shoulder lanes.

This study aims to evaluate the level of reproducibility of the marketing field. The research is motivated because many significant published research findings in various scientific areas, including marketing, have been found to be false or only partially replicable, a phenomenon labelled Reproducibility Crisis. This crisis is partly due to the strong overreliance on frequentist statistics and the misuse and misinterpretation of p-values in the Null Hypothesis Significance Testing (NHST) framework. This study offers two main contributions: first, it develops a methodological, quantitative evaluation of the most-cited published papers in marketing history in its four top journals, creating an overall index of marketing science reproducibility. Second, it analyzes how misuse and misinterpretation of p-values and frequentist statistics have undermined marketing science's reproducibility and discusses possible solutions for these problems. We selected a representative sample of the marketing literature, screening the papers using hierarchical classification criteria and the Web of Science (WoS) database to select the most-cited papers.

Global concerns have grown regarding emerging infectious diseases (EIDs) caused by previously unknown pathogens. Considering that strengthening surveillance capacity for unknown diseases is one of the core capacities for preparedness and early response to EIDs, identifying areas with poor capacity could be beneficial to prioritize regions for the improvement of surveillance. In this regard, we aimed to develop prediction models to identify high risk areas for low surveillance capacity for unknown diseases in a global scale. Unexplained death events reported between 2015 and 2019 were collected from two internet-based surveillance systems, ProMED-mail and Global Public Health Intelligence Network. From the reports, the number of reported unexplained deaths at the first report and the time gap between death and report were extracted as measures for sensitivity and timeliness of surveillance capacity, respectively. Using geographical locations of the reports and published global scale spatial data, including demographic, socioeconomic, public health and geographical variables, we fitted two boosted regression tree models to predict regions with the low sensitivity and timeliness. The performance of prediction model for the low sensitivity showed moderate validity, but in terms of the model for timeliness, the performance was unreliable. Therefore, we provided predicted risk only for low sensitivity. The mean predicted risks of low sensitivity were, respectively, 45.2%, 37.4%, 12.5%, and 3.0% in low-income, lower middle-income, upper middle-income, and high-income countries. Enhancing surveillance capacity in low-income countries is highly required, given the predicted low level of sensitivity despite the importance of early response.