The adoption of generative artificial intelligence (AI) has attracted growing attention across industries due to its potential to transform organizational processes and value creation. Despite its high applicability, however, the diffusion of generative AI in the telecommunications industry remains limited. Existing studies have largely focused on identifying individual barriers to AI adoption, providing insufficient understanding of how these barriers interact and form a complex hierarchy of constraints. Addressing this gap, this study investigates the structural interrelationships among barriers to generative AI adoption in the telecommunications industry. Based on a comprehensive literature review and expert validation, fifteen key barriers were identified. Using a Delphi-based Interpretive Structural Modeling (ISM) approach, this study examined the hierarchical influence structure among the barriers. Subsequently, the Matrix Impact Cross-reference Multiplication Applied to Classification (MICMAC) technique was employed to classify the barriers according to their driving power and dependence. The results reveal a four-level hierarchical structure in which environmental barriers play a foundational role. In particular, the absence of alignment in institutional frameworks and technical standards emerges as a root-level barrier exerting strong influence on higher-level constraints. Regulatory uncertainty and concerns about job displacement function as independent drivers linking foundational environmental conditions to execution- level constraints. Most technical, organizational, and economic barriers are concentrated at the intermediate level, forming a highly interdependent execution layer. At the top level, delays and uncertainties in decision-making regarding generative AI adoption appear as outcome-oriented barriers resulting from the cumulative effects of lower-level constraints. By highlighting that barriers to generative AI adoption in the telecommunications industry operate as a structurally connected system rather than isolated factors, this study extends existing adoption research through a structural perspective. The findings provide practical insights for telecommunications firms in prioritizing adoption strategies and offer implications for addressing institutional and regulatory conditions that shape the diffusion of generative AI.

Purpose: As the coronavirus disease 2019 (COVID-19) emerged as a global crisis in 2020, nursing students experienced an abrupt transition from offline to online classes. An in-depth understanding of the online learning experiences of nursing students can be used to reorganize nursing education during the pandemic. Therefore, this study explored the online learning experiences of nursing students during the COVID-19 pandemic. Methods: A descriptive qualitative design was employed. This study used purposive sampling to recruit 20 nursing students from a nursing college. Data were collected between November 2021 and March 2022 using semi-structured focus groups or one-to-one in-depth interviews. The collected data were analyzed using inductive content analysis. Results: Five main categories emerged from the analysis: (a) ambivalence toward rapidly changing learning methods, (b) becoming familiar with online learning, (c) facing the limitations of online learning environment, (d) discovering the charm of online learning, and (e) making suggestions for future online learning. Conclusion: Nursing students experienced disappointments and concerns about online learning classes in rapidly changing situations but also experienced an efficient aspect. Psychological support and the latest information should be provided to nursing students who may experience psychological distress during this pandemic. Additionally, learning strategies and methods should be reorganized to reflect the characteristics of nursing courses and the preferences of nursing students.

The root of Codonopsis lanceolata has been used in traditional medicine. This study was conducted to confirm the comparative effect of ethanol solvent extraction (CLE) and supercritical carbon dioxide extraction (CLS) of C. lanceolata roots. CLS had higher antioxidant than CLE. For supercritical co-solvent modified carbon dioxide extraction (CLS), it were extracted at 250 bar 50℃ 150 min at a flow rate of ethyl alcohol 3 mL/min for 90min. In addition, CLS inhibited the adipocyte differentiation of 3T3-L1 cells. When treated with the extract at a concentration of 100 μg/mL, the Wnt/β-catenin pathway reporter luciferase activity of HEK 293-TOP cells increased approximately by 3-folds compared to that of the untreated control group. Also, the treatment by CLS (50 μg/mL) showed a significant increase of involucrin expression. These results indicate that supercritical carbon dioxide extract of C. lanceolatamay serve as a cosmeceutical agent for improving skin barrier function and the treatment of obesity.

The root of Paeonia lactiflora has been used in Chinese medicine. We conducted to check the comparative qualities of ethanol solvent extraction (PLE) and supercritical carbon dioxide extraction (PLS) of P. lactiflora root. PLE had higher antioxidant and polyphenol contents than PLS. But, PLS were significantly increased peroxisome proliferator-activated receptor (PPAR)-α. In addition, PLS inhibited the adipocyte differentiation of 3T3-L1 cells. When treated with the extract at a concentration of 100 μg/mL, the Wnt/β-catenin pathway reporter luciferase activity of HEK 293-TOP cells increased approximately by 3-folds compared to that of the untreated control group. These results indicate that P. lactiflora supercritical carbon dioxide extract may serve as a cosmeceutical for improving skin barrier function and the treatment of obesity.

Ricinus communis, belongs to the family Euphorbiaceae, has been known as medicinal plants for treatment of inflammation, tumors, antidiabetic, hepatoprotective and laxative. Compared to many pharmacological studies, the effect of R. communis extract on regulating adipogenesis as therapeutic drug for treating obesity has not been reported. R. communis extract (RCE) was investigated to determine its effects on the adipogenesis by monitoring the status of Wnt/β-catenin signaling and factors involving the differentiation of adipocytes. The differentiation of 3T3-L1 cells monitored by Oil Red O staining was inhibited in concentration dependent manner by RCE. The luciferase activity of HEK 293-TOP cells containing pTOPFlash with Tcf4 response element-luciferase gene was increased approximately 2-folds by the treatment of RCE at concentrations of 100 μg/mL compared to the control. Activation of the Wnt/β-catenin pathway by RCE was further confirmed by immunocytochemical analysis which shows an increment of nuclear localization of β-catenin. In addition, safety of RCE was verified through performing neural stem cell morphology assay. Among the identified flavonoids in RCE, isoquercitrin was the most abundant. Therefore, these results indicate that the adipocyte differentiation was significantly reduced by isoquercitrin in R. communis. In this study, RCE suppresses the adipogenesis of 3T3-L1 cells via the activation of Wnt/β-catenin signaling.