Background: Interest in cardiac rehabilitation therapy has been increasing in Korea after the addition of cardiac rehabilitation as a benefit item in the National Health Insurance Service in 2017. However, few epidemiological studies have characterized cardiac rehabilitation in Korea. Objects: To assess the national epidemiological data on cardiac rehabilitation therapy in Korea from 2017 to 2023. Methods: This study analyzed MM453, a prescription code for cardiac rehabilitation therapy in the Health Insurance Review and Assessment database. The data reviewed included the total number of cases per year and the number of cardiac rehabilitation therapy prescriptions per 100,000 people, along with sex and age distribution of patients undergoing cardiac rehabilitation therapy. Results: The number of cardiac rehabilitation therapy prescriptions in Korea increased from 4,443 in 2017 to 15,646 in 2023 (252.1% increase in 7 years). The incidence per 100,000 person-years rose from 8.64 in 2017 to 30.22 in 2023. The number of males undergoing therapy increased from 3,183 (incidence: 12.35) in 2017 to 11,276 (incidence: 43.53) in 2023. The number of females undergoing therapy increased from 1,260 (incidence: 4.91) in 2017 to 4,370 (incidence: 16.89) in 2023. The highest number of patients undergoing therapy from 2017 to 2023 was observed in the 60s age group (patients: 4,747, incidence: 9.17), followed by the 70s, 50s, and > 80s age groups. Conclusion: From 2017 to 2023, the number of patients undergoing cardiac rehabilitation therapy in Korea increased consistently. The therapy is approximately 2.6 times more common in males than that in females and is predominantly administered to individuals in their 60s, followed by those in their 70s, 50s, and 80s and above.

Fueled by international efforts towards AI standardization, including those by the European Commission, the United States, and international organizations, this study introduces a AI-driven framework for analyzing advancements in drone technology. Utilizing project data retrieved from the NTIS DB via the “drone” keyword, the framework employs a diverse toolkit of supervised learning methods (Keras MLP, XGboost, LightGBM, and CatBoost) enhanced by BERTopic (natural language analysis tool). This multifaceted approach ensures both comprehensive data quality evaluation and in-depth structural analysis of documents. Furthermore, a 6T-based classification method refines non-applicable data for year-on-year AI analysis, demonstrably improving accuracy as measured by accuracy metric. Utilizing AI’s power, including GPT-4, this research unveils year-on-year trends in emerging keywords and employs them to generate detailed summaries, enabling efficient processing of large text datasets and offering an AI analysis system applicable to policy domains. Notably, this study not only advances methodologies aligned with AI Act standards but also lays the groundwork for responsible AI implementation through analysis of government research and development investments.

With the increasing indroduction and spread of invasive quarantine pests, accurate diagnosis of pests detected in quarantine sites has become crucial. DNA barcoding, a standardized method that complements morphological analysis for rapid and precise species identification, is actively researched worldwide. In this study, we established a molecular biological identification system for major pests encountered during the import and export of agricultural and forestry products. By analyzing the DNA barcode sequences of pests collected domestically and those detected in quarantine inspections, we compiled genetic information for 1,292 individuals representing 472 species, 108 families across 11 insect orders. Among these, order Lepidoptera had the highest diversity, with 251 species across 27 families. We also secured barcodes for 52 species, 24 families in order Hemiptera, and 70 species, 20 families in order Coleoptera. By constructing a comprehensive biological foundation and database for various pests detected in quarantine sites, we aim to enhance the quarantine system by enabling rapid and accurate identification of invasive pests, thereby blocking early.

In this review, we examine the latest technological developments in the utilization of truffles, a gourmet ingredient reputed to be one of the "world's three greatest delicacies," considering changing global consumption trends. Global demand for truffles is expected to increase steadily, with an average annual growth rate of 8.9% from 2023 to 2030. As truffles are expensive, the demand for truffles is expected to be concentrated in developed countries such as the United States, European countries, and Japan. In Korea, truffles are utilized in various industries, including food, functional foods, and cosmetics. Korean consumer demand for truffles has consistently remained high since 2019, and truffle products have been performing well in the market. Consequently, there exists substantial potential demand for newly developed truffle-related products and technologies. This review aims to provide objective research information through the systematic analysis of patent applications in Korea and internationally, focusing on technologies involving truffles, and can aid in setting directions for research and development.

Molten salts have gained significant attention as a potential medium for heat transfer or energy storage and as liquid nuclear fuel, owing to their superior thermal properties. Various fluoride- and chloride-based salts are being explored as potential liquid fuels for several types of molten salt reactors (MSRs). Among these, chloride-based salts have recently received attention in MSR development due to their high solubility in actinides, which has the potential to increase fuel burnup and reduce nuclear water production. Accurate knowledge of the thermal physical properties of molten salts, such as density, viscosity, thermal conductivity, and heat capacity, is critical for the design, licensing, and operation of MSRs. Various experimental techniques have been used to determine the thermal properties of molten salts, and more recently, computational methods such as molecular dynamics simulations have also been utilized to predict these properties. However, information on the thermal physical properties of salts containing actinides is still limited and unreliable. In this study, we analyzed the available thermal physical property database of chloride salts to develop accurate models and simulations that can predict the behavior of molten salts under various operating conditions. Furthermore, we conducted experiments to improve our understanding of the behavior of molten salts. The results of this study are expected to contribute to the development of safer and more efficient MSRs.

After the Fukushima nuclear accident in Japan, concerns have increased about radioactive releases from nuclear power plants (NPPs) into the environment. Analysis of annual radioactive effluent release reports (ARERRs) shows that from 2000 to 2020, abnormal releases of radioactive effluent occurred in 703 out of 1,323 Reactor·years in the United States, accounting for 53% of the total number of reactors in 63 PWRs. Furthermore, when examining incidents and malfunctions recorded in Korea’s Operational Performance Information System of Nuclear Power Plant (OPIS) during the same period, it can be estimated that abnormal releases occurred in 9 out of the 324 Reactor·years in PWRs and PHWRs. Meanwhile, database on radioactive releases from NPPs worldwide was collected, and events of abnormal/unplanned releases were investigated. Based on the data collected from 195 NPPs in 8 countries (South Korea, the United States, Japan, France, the United Kingdom, Germany, Spain, and Canada) over a period of 21 years, totaling 4,607 Reactor·years, a program called K-IRED (KHUIntegrated Radioactive Effluent Database) was developed using MS Access. Using K-IRED, three methodologies have been developed to predict abnormal events based on the annual radioactive releases for each NPPs and radionuclide (or radionuclide group). Three newly developed methodologies were applied to the 63 NPPs (1,323 Reactor·years) in the United States, categorized by radionuclides (or radionuclide groups). Assuming an increase in radioactive effluent due to abnormal events, the annual increase rate of radioactive effluent was calculated for each methodology and the results were analyzed. The optimal methodology among the three was derived, and the applicability of predicting abnormal events in other NPPs beforehand was examined. Therefore, by predicting abnormal or unplanned releases from NPPs to the environment in advance, it is possible to prevent accidents and reduce public concerns, as suggested by results of this study.

The decommissioning of Korea Research Reactor Units 1 and 2 (KRR-1&2), the first research reactors in South Korea, began in 1997. Approximately 5,000 tons of waste will be generated when the contaminated buildings are demolished. Various types of radioactive waste are generated in large quantities during the operation and decommissioning of nuclear facilities, and in order to dispose of them in a disposal facility, it is necessary to physico-chemically characterize the radioactive waste. The need to transparently and clearly conduct and manage radioactive waste characterization methods and results in accordance with relevant laws, regulations, acceptance standards is emerging. For radioactive waste characterization information, all information must be provided to the disposal facility by measuring and testing the physical, chemical, and radiological characteristics and inputting related documents. At this time, field workers have the inconvenience of performing computerized work after manually inputting radioactive waste characterization information, and there is always a possibility that human errors may occur during manual input. Furthermore, when disposing of radioactive waste, the production of the documents necessary for disposal is also done manually, resulting in the aforementioned human error and very low production efficiency of numerous documents. In addition, as quality control is applied to the entire process from generation to treatment and disposal of radioactive waste, it is necessary to physically protect data and investigate data quality in order to manage the history information of radioactive waste produced in computerized work. In this study, we develop a system that can directly compute the radioactive waste characterization information at the field site where the test and measurement are performed, protect the stored radioactive waste characterization data, and provide a system that can secure reliability.

Since high-level radioactive wastes contain long-lived nuclides and emit high energy, they should be disposed of permanently through a deep geological disposal system. In Korea, the first (2016.07) and the second (2021.12) basic plans for the management of high-level disposal systems were proposed to select sites for deep geological disposal facilities and to implement business strategies. Leading countries such as Finland, Sweden and France have developed and applied safety cases to verify the safety of deep geological disposal systems. By examining the regulatory status of foreign leading countries, we analyze the safety cases ranging from the site selection stage of the deep geological disposal system to the securing of the permanent disposal system to the investigation, analysis, evaluation, design, construction, operation, and closure. Based on this analysis, we will develop safety case elements for long-term safety of deep geological disposal systems suitable for domestic situation. To systemically analyze data based on safety cases, we have established a database of deep geological disposal system regulations in leading foreign countries. Artificial intelligence text mining and data visualization techniques are used to provide database in dashboard form rather than simple lists of data items, which is a limitation of existing methods. This allows regulatory developers to understand information more quickly and intuitively and provide a convenient interface so that anyone can easily access the analyzed data and create meaningful information. Furthermore, based on the accumulated bigdata, the artificial intelligence learns and analyzes the information in the database through deep learning, and aims to derive a more accurate safety case. Based on these technologies, this study analyzed the legal systems, regulatory standards, and cases of major international leading countries and international organizations such as the United States, Sweden, Finland, Canada, Switzerland, and the IAEA to establish a database management system. To establish a safety regulation base suitable for the domestic deep geological disposal environment, the database is provided as data to refer to and apply systematic information management on regulatory standards and regulatory cases of overseas leading countries, and it is expected that it will play a key role as a forum for understanding and discussing the level of safety of deep geological disposal system among stakeholders.

This study is aimed to provide fundamental data for expanding the scope and dimensions of Sino words research, and to secure a comprehensive perspective that encompasses the ancient, modern and dialect forms of Sino words in Korean, Chinese, Japanese, and Vietnamese. In order to achieve this goal, it is necessary to construct the wide-ranging, multi-dimensional database with maximum coverage, and this study was planned to explore specific ways to realize this. East Asian languages have exchanged cultural and linguistic influences through Chinese characters for thousands of years. Therefore, the study of Sino words requires a radial and reticular approach that can closely connect their complex historical and regional layers. However, the previous researches have revealed limitations such as inadequate examination of major languages, inappropriate use of materials, or inability to analyze rich linguistic features that exist in various dialects within Chinese or differences in words between North and South Korean. To overcome these limitations, this study confirms the need for a database that can comprehensively examine Sino words in the four languages of Korean, Chinese, Japanese, and Vietnamese, without distinguishing between base and surface forms, and encompassing all morphological forms with Chinese character elements. This database should include both archaic and contemporary, or even modern new words, as well as various dialectical forms in North and South Korea and different regions of China. To be utilized effectively in research, it should also include information on usage frequency and educational vocabulary levels, enabling the confirmation of the status of a word in contemporary language. Rather than providing definitive information like a dictionary, it is more useful to provide supplementary information such as the reference and literature, increasing the accessibility of materials for researchers and increasing the possibility of implementing the database. In response to the aforementioned need, this paper proposes the construction of a relational database consisting of 12 entity tables and presents specific procedures and methods for implementing it. Despite the difficulties of constructing a relational database for vast amounts of data and the burden on servers, we expect that a wide-ranging, multi-dimensional database of East Asian Sino words will contribute to existing research on Chinese characters, as well as vocabulary and concept research and education.

Recently, with the development of genetic technology, interest in environmental DNA (eDNA) to study biodiversity according to molecular biological approaches is increasing. Environmental DNA has many advantages over traditional research methods for biological communities distributed in the environment but highly depends on the established base sequence database. This study conducted a comprehensive analysis of the habitat status and classification at the genus level, which is mainly used in eDNA (12S rRNA, 16S rRNA, 18S rRNA, COI, and CYTB), focusing on Korean registration taxon groups (phytoplankton, zooplankton, macroinvertebrates, and fish). As a result, phytoplankton and zooplankton showed the highest taxa proportion in 18S rRNA, and macroinvertebrates observed the highest ratio in the nucleotide sequence database in COI. In fish, all genes except 18S rRNA showed a high taxon ratio. Based on the Korean registration taxon group, the gene construction of the top 20 genera according to bio density observed that most of the phytoplankton were registered in 18S rRNA, and the most significant number of COI nucleotide sequences were established in macroinvertebrates. In addition, it was confirmed that there is a nucleotide sequence for the top 20 genera in 12S rRNA, 16S rRNA, and CYTB in fish. These results provided comprehensive information on the genes suitable for eDNA research for each taxon group.