The United Methodist University (UMU) is a private institution of higher learning located in Monrovia in the West African nation of Liberia. Established in 1998 and opened in 2000, the school had 9,118 students as of 2016. UMU is certified by the Liberian government's National Commission on Higher Education to grant both bachelor's and master's degrees.
In regional economic planning, the accurate prediction of domestic tourism demand presents a critical challenge because limited access to historical time series data often causes advanced forecasting models to perform poorly. This study aims to demonstrate how linear interpolation can effectively serve as a data augmentation technique to overcome data scarcity when developing Long Short Term Memory (LSTM) networks to forecast domestic tourism arrivals. The methodology involves evaluating four distinct forecasting models using 80 months of Indonesian domestic tourism visitation data spanning from January 2019 to August 2025. These models include a statistical benchmark SARIMA (2,0,1)(0,1,1)[3] model selected via grid search out of 216 combinations and three LSTM variants run with identical random seeds. Performance evaluation is rigorously completed using MAE, RMSE, MAPE, sMAPE, and Theil’s U statistics. Key findings reveal that while unaugmented LSTM models perform poorly relative to a simple average baseline (Theil’s U = 1.38, MAPE = 24.6%), LSTMs enhanced with triple linear interpolation achieve superior predictive accuracy (MAPE = 2.6%, sMAPE = 2.6%, Theil’s U = 0.14). This approach significantly outperforms the benchmark SARIMA model (MAPE = 8.0%, Theil’s U = 0.63), which otherwise demonstrated adequate statistical validity through satisfactory residual diagnostics, including Ljung Box and Shapiro Wilk tests. In conclusion, the study demonstrates that utilizing linear interpolation as an augmentation technique is highly appropriate and effective, enabling deep learning models like LSTMs to accurately capture underlying temporal patterns from limited tourist arrival.
This paper uses a unique US dataset to analyze the demand for Directors' and Officers' liability insurance utilizing dynamic panel models. Some well-established theories propose that corporate insurance plays a role in mitigating agency problems within the corporation such as those between shareholders and managers, and managers and creditors, mitigates bankruptcy risk as well as provides real-services efficiencies. Applying dynamic panel data models, this paper uses these theories to perform empirical tests. The hypothesis that D&O insurance is entirely habit driven is rejected, while some role for persistence is still confirmed. I confirm the real-services efficiencies hypothesis and the role of insurance in mitigating bankruptcy risk. Firms with higher returns appear to demand less insurance, Although alternative monitoring mechanisms over management do not appear to play a large role, I find some support that insurance and governance are complements rather than substitutes. I fail to confirm the role of insurance in mitigating under-investment problems in growth companies.
The COVID-19 pandemic is having profound effects on college students, and those with mental health conditions are more vulnerable to the impact of this stress. Objective: To study the impact of the COVID-19 pandemic on college students' mental health. Participants: Participants (n=489) were mostly female, undergraduate, and aged 18-25. Methods: Participants completed an online survey assessing symptoms of mental health problems including hopelessness, loneliness, sadness, anxiety, sadness, and anger. Results: Approximately 81.6 % self-reported at least one negative mental health symptom. Students reported increased feelings of hopelessness (+7.8%), loneliness (+6.7%), sadness (+8.8%), depression (+2.6%), anxiety (+5.2%), and anger (+14.6%) during the pandemic than before. LGBTQ students and Black students had significantly more mental health symptoms during the pandemic than straight and White students. Conclusions: Results of this study highlight the negative impact of the pandemic and resultant changes on college students' mental health.
We extend the QCD Parton Model analysis using a factorized nuclear structure model incorporating individual nucleons and pairs of correlated nucleons. Our analysis of high-energy data from lepton Deep-Inelastic Scattering, Drell-Yan and W/Z production simultaneously extracts the universal effective distribution of quarks and gluons inside correlated nucleon pairs, and their nucleus-specific fractions. Such successful extraction of these universal distributions marks a significant advance in our understanding of nuclear structure properties connecting nucleon- and parton-level quantities.
This research examines the relationship between a green economy—defined as an economy that promotes sustainable development through low-carbon, resource-efficient, and socially inclusive practices—and food safety across 37 African countries from 2005 to 2020. Drawing on data from the Food and Agricultural Organization (FAO), the Country Policy and Institutional Assessment (CPIA), and World Development Indicators, this study employs the generalized method of moments (GMM) approach to address endogeneity issues inherent in economic analyses. The findings indicate that a shift toward a greener economy significantly enhances food safety, with each one-point improvement in green economic indicators associated with a 0.24
