The Cisadane Watershed is in a critical state, which has expanded residential areas upstream of Cisadane. Changes in land use and cover can impact a region's hydrological characteristics. The Soil and Water Assessment Tool (SWAT) is a hydrological model that can simulate the hydrological characteristics of the watershed affected by land use. This study aims to evaluate the impact of land use change on the hydrological characteristics of the Cisadane watershed using SWAT under different land use scenarios. The models were calibrated and validated, and the results showed satisfactory agreement between observed and simulated streamflow. The main river channel is based on the results of the watershed delineation process, with the watershed boundary consisting of 85 sub-watersheds. The hydrological characteristics showed that the maximum flow rate (Q max) was 12.30 m³/s, and the minimum flow rate (Q min) was 5.50 m³/s. The study area's distribution of future land use scenarios includes business as usual (BAU), protecting paddy fields (PPF), and protecting forest areas (PFA). The BAU scenario had the worst effect on hydrological responses due to the decreasing forests and paddy fields. The PFA scenario yielded the most favourable hydrological response, achieving a notable reduction from the baseline BAU in surface flow, lateral flow, and groundwater by 2%, 7%, and 2%, respectively. This was attributed to enhanced water infiltration, alongside increases in water yield and evapotranspiration of 3% and 15%, respectively. l Therefore, it is vital to maintain green vegetation and conserve land to support sustainable water availability.

This study meticulously explores the crucial elements precipitating corporate failures in Taiwan during the decade from 1999 to 2009. It proposes a new methodology, combining ANOVA and tuning the parameters of the classification so that its functional form describes the data best. Our analysis reveals the ten paramount factors, including Return on Capital ROA(C) before interest and depreciation, debt ratio percentage, consistent EPS across the last four seasons, Retained Earnings to Total Assets, Working Capital to Total Assets, dependency on borrowing, ratio of Current Liability to Assets, Net Value Per Share (B), the ratio of Working Capital to Equity, and the Liability-Assets Flag. This dual approach enables a more precise identification of the most instrumental variables in leading Taiwanese firms to bankruptcy based only on financial rather than including corporate governance variable. By employing a classification methodology adept at addressing class imbalance, we substantiate the significant influence these factors had on the incidence of bankruptcy among Taiwanese companies that rely solely on financial parameters. Thus, our methodology streamlines variable selection from 95 to 10 critical factors, improving bankruptcy prediction accuracy and outperforming Liang's 2016 results.

Formation of the latest scientific and methodological principles and the determination of the most important directions of the paradigm of the analysis of artistic creativity and text have been represented as actual problems of the theory of modern Kazakh literary criticism. The purpose of the work is to consider and analyze the modern concepts of Kazakh literary criticism, to evaluate the contribution of scientists from the period of independence of Kazakhstan in the development of theoretical analysis and interpretation of the artistic originality of national literature. The article discusses new trends in the theory of Kazakh literary criticism, changes in methodology, which are due to the leading positions of world literary criticism. In this regard, the article offers an analytical review of the main scientific and theoretical studies in the field of literary criticism, defines the evolution of the concepts of scientific and theoretical thought, identifies the principles and main aspects of the study of literature in a new way, shows certain achievements in close relationship with historical stages, as well as tasks future research; literary-theoretical and philosophical-aesthetic searches in modern Kazakh literary criticism are evaluated, the prospects for its development are determined.

Food safety in supply chains remains a critical concern due to the complexity of global distribution networks. This study develops a conceptual framework to evaluate how food safety risks influence supply chain performance through predictive analytics. The framework identifies and minimizes food safety risks before they cause serious problems. The study examines the impact of food safety practices, supply chain transparency, and technological integration on adopting predictive analytics. To illustrate the complex dynamics of food safety and supply chain performance, the study presents supply chain transparency, technological integration, and food safety practices and procedures as independent variables and predictive analytics as a mediator. The results show that supply chain managers' capacity to anticipate and control risks related to food safety can be improved by predictive analytics, leading to safer food production and distribution methods. The research recommends that businesses create scalable cloud-based predictive model solutions, combine data sources, and employ cutting-edge AI and machine learning tools. Companies should also note that strong, data-driven approaches to food safety require cooperative data sharing, regulatory compliance, training initiatives and ongoing improvement.

This study addresses the rising concerns of technostress experienced by teachers due to the increased reliance on educational technology in both classroom and online settings. Technostress, defined as the adverse psychological effects arising from the use of information communication technologies, has been documented to impact teacher performance and overall well-being. Despite the importance of educational technology in enhancing teaching and learning experiences, many educators report elevated levels of anxiety, stress, and pressures associated with their use of these tools. This study presents practical strategies to help teachers alleviate or prevent technostress while using educational technology. This study used a quantitative approach with a survey conducted among 113 university and schoolteachers. The data analysis included frequency and percentage distribution of categorical variables, Cronbach's alpha for reliability, chi-square test, and exploratory factor analysis to identify strategies for symptom prevention. The results indicated that while many teachers experienced symptoms of technostress due to several factors, some did not. The study concluded with specific strategies, and many teachers agreed highly. The implications of this study are profound for educational institutions, policymakers, and teacher training programs as they underscore the necessity of providing comprehensive training, support, and resources to help educators manage technostress effectively. By integrating these strategies into professional developmental programs and fostering a supportive teaching environment, schools and universities can promote better mental health for teachers, improving students' educational outcomes.

This study investigates the role of Chat-GPT with augmented reality applications in enhancing tourism experiences in Thailand, focusing on behavioral intentions and innovation adoption to reduce stress in the tourism industry. The research addresses two key objectives: identifying factors driving consumers' behavioral intentions to adopt AR apps and evaluating the robustness of a modified innovation framework for analyzing these intentions. A conceptual model integrating innovativeness, attitudes, perceived enjoyment, and revisit intentions was developed and tested using Structural Equation Modeling with data from 430 Thai tourists who have one to three years of mobile application experience. The findings highlight that service and technology innovation significantly influence perceived enjoyment and attitude, which in turn mediate the impact on behavioral intention to adopt augmented reality applications. At a significance level of p < 0.001, perceived enjoyment and attitude were identified as critical determinants of BI, underscoring the importance of intrinsic user experiences. Tourists are more likely to adopt augmented reality technologies based on personal perceptions and enjoyment rather than external recommendations. This research provides actionable insights for stakeholders in the tourism technology ecosystem, including technology providers, marketers, and policymakers. By emphasizing the interplay of social, emotional, and hedonic factors in shaping user attitudes, the study introduces a robust framework for advancing augmented reality applications in tourism. The findings underscore the importance of user-centric design to drive technology adoption and offer strategic guidance for developers and entrepreneurs aiming to enhance tourism experiences through innovative augmented reality solutions.