High-risk pregnancies are a global concern, with maternal and fetal well-being at the forefront of clinical care. Pregnancy’s three trimesters bring distinct changes to mothers and fetal development, impacting maternal health through hormonal, physical, and emotional shifts. Fetal well-being is influenced by organ development, nutrition, oxygenation, and environmental exposures. Effective management of high-risk pregnancies necessitates a specialized, multidisciplinary approach. To comprehend this integrated approach, a comparative literature analysis using Atlas.ti software is essential. Findings reveal key aspects vital to high-risk pregnancy care, including intervention effectiveness, case characteristics, regional variations, economic implications, psychosocial impacts, holistic care, longitudinal studies, cultural factors, technological influences, and educational strategies. These findings inform current clinical practices and drive further research. Integration of knowledge across multidisciplinary care teams is pivotal for enhancing care for high-risk pregnancies, promoting maternal and fetal well-being worldwide.

In the face of growing competition, industrial and commercial firms need more effective strategies to gain competitive advantages. This study investigates the role of enterprise risk management (ERM) as a mediator in highlighting the significance of innovation capability on profitability in industrial and commercial firms listed on the Amman Stock Exchange (ASE). Data were collected from 244 respondents using a standardized questionnaire and analyzed with SPSS software. The results indicate that the innovation capability has an impact on profitability in industrial and commercial firms, as well as their ERM practices. Additionally, ERM mediates the relationship between innovation capability and profitability. Firms that adopt distinctive innovation strategies tend to maintain formal ERM strategies, which in turn enhance market superiority and profitability. This research offers some significant managerial ramifications that may be essential for business owners, executives, and decision-makers involved in the development of firms.

The construction of gas plants often experiences delays caused by various factors, which can lead to significant financial and operational losses. This research aims to develop an accurate risk model to improve the schedule performance of gas plant projects. The model uses Quantitative Risk Analysis (QRA) and Monte Carlo simulation methods to identify and measure the risks that most significantly impact project schedule performance. A comprehensive literature review was conducted to identify the risk variables that may cause delays. The risk model, pre-simulation modeling, result analysis, and expert validation were all developed using a Focused Group Discussion (FGD). Primavera Risk Analysis (PRA) software was used to perform Monte Carlo simulations. The simulation output provides information on probability distribution, histograms, descriptive statistics, sensitivity analysis, and graphical results that aid in better understanding and decision-making regarding project risks. The research results show that the simulated project completion timeline after mitigation suggested an acceleration of 61–65 days compared to the findings of the baseline simulation. This demonstrates that activity-based mitigation has a major influence on improving schedule performance. This research makes a significant contribution to addressing project delay issues by introducing an innovative and effective risk model. The model empowers project teams to proactively identify, measure, and mitigate risks, thereby improving project schedule performance and delivering more successful projects.

In this study, we explore the impact of contemporary bank run incidents on stock market performance, taking into consideration insured deposit concentration. Specifically, we use data from the recent downfall of the Silicon Valley Bank (SVB). By employing event study methods with the mean-adjusted return model and market models, we evaluate the cumulative abnormal returns (CARs). Our findings reveal a substantial negative CAR for all the listed companies in our sample, suggesting that the SVB crisis adversely affected stock returns. Further analysis shows an even more pronounced effect on the banking sector and that banks with a high concentration of insured deposits experienced economically and statistically less negative CARs. We also find that the response by the Treasury Department, the Federal Reserve, the Federal Deposit Insurance Corporation, and other agencies—aimed at fully safeguard all depositors—led a rebound in CARs. Our results highlight the importance of deposit insurance policy and regulatory responses in protecting the financial system during panic events.

Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.

This study aims to evaluate the relationship between financial resilience, exchange rate, inflation, and economic growth from 1996 to 2022 using secondary data from the World Bank. The analysis method uses vector autoregressive to understand the causality dynamics between these variables. The results show that past economic growth positively impacts current economic conditions, but an increase in the exchange rate can hinder economic growth. The exchange rate also tends to be influenced by previous values, but high economic growth does not always increase the exchange rate. Previous conditions significantly affect financial resilience and can be strengthened by a strong currency. Meanwhile, inflation has an inverse relationship with economic growth, where past inflation seems to suppress current inflation, which price stabilization policies can cause. From an institutional economics perspective, this study provides an understanding of the interaction between various economic factors in the structural framework and policies that regulate economic activities. The impulse response function (IRF) shows that economic growth can react strongly to sudden changes, although this reaction may not last long. The exchange rate fluctuates with economic changes, reflecting market optimism and uncertainty. Financial resilience may be strong initially but may weaken over time, indicating the need for policies to strengthen the financial system to ensure economic stability. Furthermore, the role of social capital in economic resilience is highlighted as it can amplify the positive effects of a robust institutional framework by fostering trust and collaboration among economic actors. Inflation reacts differently to economic changes, challenging policymakers to balance growth and price stability. Overall, the IRF provides insights into how economic variables interact with each other and react to sudden changes, albeit with some uncertainty in the estimates. The forecast error decomposition variance (FEVD) analysis in this study reveals that internal factors initially influence economic growth, but over time, external factors such as the exchange rate, financial resilience, and inflation come into play. The exchange rate, which was initially volatile due to internal factors, becomes increasingly influenced by economic growth, indicating a close relationship between the economy and the foreign exchange market. From an institutional economics perspective, financial resilience, which was initially stable due to internal factors, becomes increasingly dependent on global economic conditions, suggesting the importance of a solid institutional framework for maintaining economic stability. In addition, inflation, which was initially explained by economic growth and exchange rates, has gradually become more influenced by financial resilience, indicating the importance of effective monetary policy in controlling inflation. This study highlights the importance of understanding how economic variables influence each other for effective economic governance. Integrating institutional economics and social capital perspectives provides a comprehensive framework for enhancing financial resilience and promoting sustainable economic development in Indonesia.