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 paper, we examine a possible application of ordered weighted average (OWA for short) aggregation operators in the insurance industry. Aggregation operators are essential tools in decision-making when a single value is needed instead of a couple of features. Information aggregation necessarily leads to information loss, at least to a specific extent. Whether we concentrate on extreme values or middle terms, there can be cases when the most important piece of the puzzle is missing. Although the simple or weighted mean considers all the values there is a drawback: the values get the same weight regardless of their magnitude. One possible solution to this issue is the application of the so-called Ordered Weighted Averaging (OWA) operators. This is a broad class of aggregation methods, including the previously mentioned average as a special case. Moreover, using a proper parameter (the so-called orness) one can express the risk awareness of the decision-maker. Using real-life statistical data, we provide a simple model of the decision-making process of insurance companies. The model offers a decision-supporting tool for companies.

During the COVID-19 pandemic, individuals and their families faced various risk factors, which in some cases resulted in divorce. Adolescents in such families had to grapple with COVID-19 across the world, the risk factors faced by adolescents have largely been under-risk factors associated with COVID-19 and divorce. Despite the rise of divorce during studied, especially among adolescents in South Africa. This study aimed to explore the risk factors experienced by adolescents from divorced households during the COVID-19 pandemic and make recommendations for policy and development. This study employed a phenomenological research design in alignment with qualitative research. Purposive sampling was used to recruit five female adolescents in Johannesburg. Data was collected using semi-structured interviews and focus groups. Data was analyzed thematically using Braun and Clarke’s six steps of data analysis. The findings revealed that conflict at home, mental illness, physical and social isolation, a lack of paternal support, and diminished educational performance emerged as risk factors faced by the participants. These findings underscore the need for psychological interventions to help address the risk factors faced by adolescents whose parents divorced during the pandemic and those who face similar circumstances during future crises.

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.

Family violence is the act that causes harm, suffering, or death to members of the family group, especially if they are in a situation of vulnerability due to characteristics associated to age or physical condition. Objective: The social characteristics of aggressors were associate in the risk level of victims of family violence in the city of Arequipa, Peru. Method: The study was descriptive, quantitative, and non-experimental. A total of 205 randomly selected judicial files of aggressors reported for domestic violence were evaluated. The data were secondary, and the chi-square test (association of categorical variables) was used for statistical analysis. Results: A moderate risk level (31.2%) was found, with a tendency to be severe and very severe (49.5%). Likewise, the most observed types of violence are physical and psychological violence (89.3%) and sexual abuse (10.7%). The female aggressor exerts mild violence, while the male aggressor exerts moderate to extreme severe violence, causing more harm to the victim. The profile of the aggressor with low or high education, with high or low incomes, and who occupies a house or only one room can be associated the level of violence that occurs. Conclusion: Men are more likely to attack women, and similarly, female aggressors tend to target men more frequently. Moreover, men exhibit a higher tendency to attack their partners, including wives, cohabitants, and ex-partners, whereas women tend to target a broader range of family members, including parents, children, grandparents, nephews, cousins, as well as in-laws such, brothers-in-law and other relatives.