Purpose: To collect and analyze microplastics in the atmosphere, a preprocessing method is necessary. Currently, reliable preprocessing methods recognized in academia include oxidation treatment and density separation. Research design, data and methodology: Oxidation treatment is a process for removing organic matter in the sample. By adding 20 mL of H₂O₂ and 20 mL of Fenton oxidation solution to the sample and heating it at 60℃ for 2 hours, the organic matter in the sample is oxidized and removed. Density separation is a process for removing inorganic matter in the sample. By adding 40 mL of ZnBr₂ density separation solution to the sample and allowing it to settle in a separatory funnel for 24 hours, the supernatant is collected for filtration. At this stage, the stopcock at the bottom of the separatory funnel is opened to remove the precipitated inorganic matter based on density differences. Results: Additionally, before applying these preprocessing methods, a resuspension process is required to detach microplastics from the actual sample. This is achieved through sonication for 10 minutes. Conclusions: The objective of this study is to investigate the current status of FT-IR analysis in Korea and to determine the optimal analytical method.

In response to the increasing emphasis on childcare within public institutions, this study examines the impact of daycare center directors' coaching leadership on teacher-infant interactions, mediated by the psychological well-being of teachers. A survey was conducted with 251 childcare teachers from daycare centers located in the Seoul and Gyeonggi regions. Data collection was conducted using a written survey or an online questionnaire after the researcher gave prior consent to the daycare center visit. The collected data were analyzed using IBM SPSS 26.0. Analysis included factor analysis, reliability analysis, descriptive statistics, t-test, variance analysis, correlation analysis, and regression analysis. The results indicate that daycare directors' coaching leadership significantly influences teachers' psychological well-being. Specifically, the goals and feedback from directors, along with their belief in teachers' growth potential, positively impact teachers' well-being. This well-being, in turn, affects teacher-infant interactions, with self-acceptance closely linked to these interactions. Additionally, directors' coaching leadership directly influences teacher-infant interactions and indirectly affects teachers' psychological well-being. These findings indicate that effective coaching leadership can enhance teachers' well-being and improve their interactions with infants. Therefore the study underscores the importance of directors' coaching leadership in daycare operations and provides foundational data for developing effective coaching strategies that benefit childcare settings. It suggests ways to improve teacher-infant interactions, ultimately enhancing childcare quality.

Background: Falls among the elderly represent a significant public health challenge, substantially impacting morbidity, mortality, and healthcare expenditures. This study aims to provide a comprehensive understanding of fall patterns and associated risk factors among the elderly population in South Korea. Methods: Data from the 2021 Korean Community Health Survey, including 71,734 participants aged 65 and older, were analyzed using a zero-inflated negative binomial (ZINB) regression model to simultaneously model the occurrence and frequency of falls. Results: Approximately 16.73% of participants experienced at least one fall-related injury in the past year. Advancing age (1.7% for each one-year increase), male (19.2% versus female), no formal education (11% to 19% versus elementary to junior high school graduate), poverty (23.8%), poor (86.2%) or fair (17.0%) self-rated health, diabetes mellitus (29.7%), underweight (17.7%), and obese (13.6%) were significantly associated with higher incidence rate of recurrent falls. Conclusions: This study highlights the complex interplay of sociodemographic and health-related factors in fall risk among the elderly. The findings underscore the importance of multifaceted fall prevention strategies that consider both individual and societal factors, particularly targeting high-risk groups such as the oldest old, those with lower socioeconomic status, and individuals with chronic diseases.

Purpose: This study evaluates the impact of car wash operations on surrounding soil properties in Gilgit City. The research focuses on key soil parameters, including pH, electrical conductivity (EC), soil organic matter (SOM), soil organic carbon (SOC), and soil texture. Understanding these impacts is crucial for assessing potential soil degradation due to car wash effluents. Research Design, Data, and Methodology: A reconnaissance survey identified three car wash sites: Danyore, Dumiyal, and Nagaral. Soil samples were collected from these locations and analyzed for pH, EC, SOM, SOC, and texture composition. One-way analysis of variance (ANOVA) was conducted to determine mean differences among sites, while Pearson's correlation coefficient was used to examine relationships between soil properties. Results: Significant variations were observed in soil properties across the study sites. The highest pH was recorded in Danyore (7.7), followed by Dumiyal (7.5) and Nagaral (7.2). EC was highest in Dumiyal (5.1 mS/m), followed by Nagaral (2.9 mS/m) and Danyore (2.3 mS/m). The highest SOM and SOC levels were found in Nagaral (2.6%, 1.5%), followed by Dumiyal (2.5%, 1.4%) and Danyore (1.9%, 1.1%). Soil texture analysis revealed that sand content was highest in Danyore (73.2%), while silt content was highest in Dumiyal (61.2%). Clay content remained constant across all sites. Conclusion: The findings indicate that car wash activities significantly alter soil properties, leading to chemical and physical degradation. Increased EC levels and altered SOM and SOC contents suggest contamination from car wash effluents, which can negatively impact soil health. These results highlight the need for implementing environmentally friendly car wash practices, including wastewater treatment, to mitigate soil degradation and preserve soil quality in urban areas.

Purpose: This study examines global trends and interdependencies in healthcare IT from 2011 to 2024, focusing on Electronic Medical Records (EMRs), Health Information Systems (HIS), Patient Data, Data Security, and Interoperability. The aim is to identify temporal patterns, correlations, and future trends while integrating public sentiment analysis. EMRs and interoperability received predominantly positive sentiment, while patient data and data security raised concerns related to privacy and cybersecurity threats. Research Design and Methods: Using Google Trends data, this study analyzed temporal trends, Pearson correlations, and time-series forecasting. Sentiment analysis assessed public perception of healthcare IT concepts. Data was processed using Python-based statistical, machine learning, and natural language processing (NLP) tools. A quantitative, exploratory approach was used to examine the evolution of search interest and sentiment. Research Results: "Patient Data" showed the highest interest, reflecting its central role in healthcare IT. Sentiment analysis revealed negative perceptions of data security, highlighting privacy concerns. Data Security (0.91) and Interoperability (0.77) strongly correlated, indicating security's role in data exchange. EMRs and interoperability were viewed positively, emphasizing their efficiency in patient care and workflow integration. Predictive modeling suggests increasing interest in healthcare IT, particularly in security and interoperability improvements. Conclusion: The findings highlight the need for secure and interoperable healthcare IT systems. Policymakers should strengthen security protocols, enhance interoperability, and improve public trust to facilitate a more secure, efficient, and patient-centered digital transformation.

This study presents a comprehensive analysis of AI service adoption in the food industry through a wellness-oriented perspective, utilizing a systematic literature review of publications from 2014 to 2024. Through an extensive examination of relevant literature, we identify three critical dimensions: the transformative impact of AI on consumer health and well-being, the fundamental challenges in AI service implementation, and strategic frameworks for successful adoption. Our findings demonstrate that AI services manifest primarily in three distinct forms: process automation, cognitive insights, and cognitive engagement, with cognitive insights emerging as the predominant form, particularly in quality control and supply chain optimization. The research reveals significant challenges, including data quality management, organizational resistance, and workforce adaptation, while emphasizing the critical importance of balancing technical innovation with wellness value creation. We contribute to the existing literature by developing an integrated theoretical framework that synthesizes technological, organizational, and wellness perspectives in AI adoption. The study provides both theoretical contributions through a novel wellness-centric approach to AI adoption research and practical implications by offering strategic guidelines for food industry practitioners. Our findings suggest that successful AI implementation requires a holistic strategy that encompasses technological advancement, organizational transformation, and sustainable wellness value creation, thereby advancing the theoretical understanding of AI.

Purpose: This study examines long-term trends and regional variations in SO₂ concentrations across Korean cities from 2014 to 2023. It evaluates air pollution control policies and identifies key factors in SO₂ reduction to provide insights for sustainable environmental management. Research Design & Data: The study employs descriptive statistical analysis, time-series modeling, correlation analysis, and boxplot & violin plot visualizations to assess SO₂ concentration data. It also examines regional pollution variations, seasonal fluctuations, and policy effectiveness to determine key influences on urban air quality. Research Results: The findings indicate a statistically significant decline in SO₂ concentrations in most cities, particularly Seoul, Busan, etc. due to stricter emission policies and industrial restructuring. However, Gwangju exhibited a stable trend, suggesting limited impact from regulations. The boxplot analysis highlights pollution disparities, with higher variability in industrial hubs like Ulsan. The violin plot analysis shows a steady decline in SO₂ pollution, with high variability in earlier years (2014-2016) becoming more uniform in 2020-2023. This suggests that policy enforcement and industrial regulations have reduced pollution disparities. Correlation analysis reveals weak associations between meteorological factors and SO₂ levels, reinforcing the dominant role of policy enforcement and industrial emissions in air pollution trends. Conclusion: South Korea's air pollution control policies have significantly reduced SO₂ levels, yet regional disparities persist, especially in industrial cities. Strengthened regional collaboration, targeted emission regulations, and improved air quality management are essential for sustaining progress. Future policies should focus on integrated pollution control strategies, stricter industrial emission limits, and advanced monitoring systems to ensure continued environmental and public health benefits.

Purpose: This study investigates the primary causes of odor pollution in rural South Korea and its impact on community welfare. Odor pollution, mainly caused by livestock farms, waste dumping, and sewage treatment facilities, poses significant challenges to residents' health, stress levels, and quality of life, complicating sustainable rural development. Research Design & Data: A mixed-methods approach was used, combining surveys of 4,000 households (2,800 rural, 1,200 urban), field observations, and secondary data analysis. The primary data, collected by the Rural Development Administration of South Korea, were analyzed as secondary data. Statistical tools, including descriptive statistics, correlation analysis, and t-tests, explored relationships between odor exposure, proximity to sources, and stress levels. This statistical analysis was conducted using Python statistical program version 3.9. Research Results: Livestock facilities emerged as the leading source of odor pollution, exceeding contributions from factories, waste dumping, and sewage treatment plants. Residents within 1-3kilometers of odor sources reported elevated stress levels and frequent health issues. Rural residents experienced higher stress levels than urban counterparts due to greater exposure and fewer mitigation measures. Statistical analysis revealed a strong negative correlation between proximity to odor sources and stress levels. Conclusion: Effective odor pollution management requires advanced mitigation technologies, stricter regulations, and community-driven strategies to improve health outcomes, reduce stress, and ensure sustainable rural living conditions. This study provides critical insights for policy makers, fostering healthier, more equitable rural communities.