Richard’s equation was approximated by finite-difference numerical scheme to model water infiltration profile in variably unsaturated soil^[1]. The published data of Philip’s semi-analytical solution was used to validate the simulated results from the numerical scheme. A discrepancy was found between the simulated and the published semi-analytical results. Morris method as a global sensitivity tool was used as an alternative to local sensitivity analysis to assess the results discrepancy. Morris method with different sampling strategies were tested, of which Manhattan distance method has resulted a better sensitivity measures and also a better scan of input space than Euclidean method. Moreover, Morris method at p = 2 , r = 2 and Manhattan distance sampling strategy, with only 2 extra simulation runs than local sensitivity analysis, was able to produce reliable sensitivity measures (μ^*, σ). The sensitivity analysis results were cross-validated by Sobol’ variance-based method with 150,000 simulation runs. The global sensitivity tool has identified three important parameters, of which spatial discretization size was the sole reason of the discrepancy observed. In addition, a high proportion of total output variance contributed by parameters β and θ_s is suggesting a greater significant digits to reduce its input uncertainty range.

This study examines the effectiveness of Kazakhstan’s grant funding system in supporting research institutions and universities, focusing on the relationship between funding levels, expert evaluations, and research outputs. We analyzed 317 projects awarded grants in 2021, using parametric methods to assess publication outcomes in Scopus and Web of Science databases. Descriptive statistics for 1606 grants awarded between 2021 and 2023 provide additional insights into the broader funding landscape. The results highlight key correlations between funding, evaluation scores, and journal publication percentiles, with a notable negative correlation observed between international and national expert evaluations in specific scientific fields. A productivity analysis at the organizational level was conducted using non-parametric methods to evaluate institutional efficiency in converting funding into research output. Data were manually collected from the National Center of Science and Technology Evaluation and supplemented with publication data from Scopus and Web of Science, using unique grant numbers and principal investigators’ profiles. This comprehensive analysis contributes to the development of an analytical framework for improving research funding policies in Kazakhstan.

This study aims to develop a robust prioritization model for municipal projects in the Holy Metropolitan Municipality (Makkah) to address the challenges of aligning short-term and long-term objectives. The research explores How multi-criteria decision-making (MCDM) techniques can prioritize municipal projects effectively while ensuring alignment with strategic goals and local needs. The methodology employs the analytic hierarchy process (AHP) and exploratory factor analysis (EFA) to ensure methodological rigor and data adequacy. Data were collected from key stakeholders, including municipal planners and community representatives, to enhance transparency and reliability. The model’s validity was assessed through latent factor analysis, confirming the relevance of identified criteria and factors. Results indicate that flood prevention projects are the highest priority (0.4246), followed by road projects (0.3532), park construction (0.1026), utility projects (0.0776), and digital transformation (0.0416). The study highlights that certain factors are critical for evaluating and prioritizing municipal projects. “Capacity and Demand” emerged as the most influential factor (0.5643), followed by “Strategic Alignment” (0.2013), “Project Interdependence” (0.1088), “Increasing Investment” (0.0950), and “Risk” (0.0306). These findings are significant as they offer a structured, data-driven approach to decision-making aligned with Saudi Vision 2030. The proposed model optimizes resource allocation and project selection, representing a pioneering effort to develop the first prioritization framework specifically tailored to Makkah’s unique municipal needs. Notably, this is the first study to establish a prioritization method specifically for Makkah’s municipal projects, providing valuable contributions to the field.

This research uses both quantitative and qualitative research methodologies to examine the complex factors affecting community resilience in various settings. In this case, the research explores how social cohesion, governance effectiveness, adaptability, community involvement, and the specified difficulties influence resilience results by using the five pillars of resilience as variables. Descriptive and inferential statistics are used to test hypotheses on the relationships between social cohesion, governance effectiveness, adaptive capacity, and community resilience variables. Qualitative data provides further insights into the quantitative results by providing broader views and experiences of the community. The study shows how social capital is important in increasing community capacity, stressing the importance of social relations and trust in developing community solutions to disasters. Another major factor that stands out is the governance factor that ensures that decisions are made, and actions taken in line with the community’s best interest in improving its ability to prepare for and respond to disasters. Adaptive capacity is seen as a key component of resilience and this paper emphasizes the importance of communities to come up with measures that can be adjusted to the changing circumstances. In summary, this study enriches theoretical understanding and offers practical applications of the processes that can enhance community resilience based on the principles of social inclusion, sound governance, and context-specific solutions.

In order to understand the finishing effect of Waterborne Acrylic Paint under different painting methods and amount, bamboo-laminated lumber for furniture was coated with waterborne acrylic paint, then the effects of different painting methods and amount on the drying rate, smoothness, hardness, adhesion and wear resistance of the paint film were investigated. Further, the mechanism of film formation was described by thermal property analysis using thermogravimetry and differential scanning calorimeter. The results show that different painting methods have little effect on film properties, the drying time of primer and topcoat are not affected by them, which is 8/8.5 min for primer surface/solid and 6.5/7 min for topcoats. The film surface hardness and adhesion can reach B and 0 grade, the best wear resistance of the film is 51.24 mg·100 r⁻¹ when using one-layer primer one-layer topcoat. Different coating amount has great influence on film properties, the drying speed of the film increases with the increase of the painting amount. The film properties reach the best when the painting amount is 80 g/m², while too little painting amount leads to the decrease of hardness, and too much leads to the wear resistance weaken. Thermal analysis of the primer and topcoat show that water decomposition occurs at 100 ℃ and thermal decomposition of organic components occur at 350 ℃. Topcoats have better thermal stability than primers higher than that of topcoat, the topcoat displayed better thermal stability than the primer.

The study aims to examine the labor market challenges and motivational factors for employee retention through the example of a small machinery company in Hungary. In recent years, Hungary’s labor market has faced significant difficulties, particularly due to the COVID-19 pandemic, which resulted in temporary unemployment followed by labor shortages. The research aims to identify the motivational, welfare, and financial factors that contribute to employee retention. Due to the small sample size, we did not investigate the relationships concerning loyalty, commitment, and performance. The research methods included comprehensive data collection at a machinery company employing 24 people located near the Austrian-Hungarian border. During the data collection, we conducted a questionnaire survey that included questions related to benefits, performance, commitment, and loyalty. The collected data were processed by calculating weighted averages and differences. The results indicate that flexible working hours and easy accessibility to the workplace are of utmost importance to employees. There is also a significant demand for performance-based pay and diverse, flexible benefit packages. Employees require both formal and informal professional recognition, such as praise and awards. The research has practical significance for both organizational management and employee well-being. Understanding employee opinions and implementing measures based on these can have four primary effects: improvement in employee performance, reduction in turnover, increase in organizational commitment, and enhancement of the company’s positive perception.