Sustainability has become increasingly important in recent decades and has become a key concept in various areas of society. The early integration of sustainability principles into education is of crucial importance, as the elementary school years represent a decisive phase in children's development. During this phase, fundamental values, attitudes, and behaviors are formed that will have a significant impact on later lives and the relationship with the environment. Elementary school offer a unique opportunity to reach people from different social backgrounds and thus impart a common basic knowledge that can serve as a basis for shaping a sustainable society. Elementary schools are therefore an ideal place to introduce children to the principles of sustainability and sensitize them to the challenges of the 21st century. The aim of the study is to explore the current state of sustainability education in elementary school. It takes a closer look at whether elementary school students are old enough to be confronted with sustainability, what methods already exist and what the challenges are in implementing sustainability education. The basis for the study is an online survey conducted at 60 different elementary school in the state of Baden-Wuerttemberg in Germany. In conclusion, while there is room for improvement, the survey results suggest a growing awareness of the significance of sustainability education in elementary schools. The findings call for targeted efforts to enhance curriculum integration, teacher training, and resource provision to promote a more sustainable and environmentally conscious generation of students in Baden-Wuerttemberg.

Purpose: This research aims to explore the phenomenon of job-hopping in the engineering sector in Penang, Malaysia, focusing on how factors like positive work culture, compensation and benefits, and job satisfaction influence an engineer’s propensity to frequently change jobs. Design/methodology/approach: The study adopted a cross-sectional survey design, targeting 200 engineers in Penang. It was grounded in Herzberg’s Motivation-Hygiene Theory. Data collection was conducted using online questionnaires, which were adaptations of instruments used in previous research. Statistical analysis, including Pearson correlation and multiple linear regression, was performed using SPSS software. Findings: The Pearson correlation analysis revealed significant negative relationships between positive work culture, compensation and benefits, job satisfaction, and the tendency to job-hop. However, in the regression analysis, only job satisfaction emerged as a significant predictor of job-hopping behavior. This finding suggests that while factors like work culture and compensation/benefits contribute to the overall work environment, they do not primarily drive job mobility among engineers in this region. The study indicates that job satisfaction plays a more crucial role in influencing engineers’ decisions to change jobs frequently. Conclusion: The study enriches the field of organizational psychology by applying Herzberg’s theory to understand job-hopping behavior in the engineering sector. For organizations in Penang, the findings highlight the importance of enhancing job satisfaction as a strategy for reducing job-hopping and retaining talent. This insight is valuable for both academic research and practical application in the industry, emphasizing the critical role of job satisfaction in curbing job-hopping tendencies within the engineering field.

This study examines the impact of innovation governance and policies on government funding for emerging science and technology sectors in Saudi Arabia, addressing key bureaucratic, regulatory, and cultural barriers. Using a mixed-methods approach, the research integrates qualitative insights from stakeholder interviews with quantitative survey data to provide a comprehensive under-standing of the current innovation landscape. Findings indicate a high level of policy awareness among stakeholders but reveal significant challenges in practical implementation due to bureaucratic inefficiencies and stringent regulations. Cultural barriers, such as a risk-averse mindset and traditional business practices, further impede innovation. Successful initiatives like the National Transformation Program (NTP) demonstrate the potential for well-coordinated efforts, highlighting the importance of regulatory reform and cultural shifts towards entrepreneurship. Strategic recommendations include streamlining bureaucratic processes, enhancing policy coordination, and fostering a culture of innovation through education and stakeholder engagement. This study contributes to the existing literature by offering actionable insights to enhance innovation governance, supporting Saudi Arabia’s Vision 2030 goals.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

Proposed herein is an environment-friendly method to realize oil/water separation. Nylon mesh is exposed to atmospheric pressure plasma for surface modification, by which micro/nano structures and oxygen-containing groups are created on nylon fibers. Consequently, the functionalized mesh possesses superhydrophilicity in air and thus superoleophobicity underwater. The water pre-wetted mesh is then used to separate oil/water mixtures with the separation efficiency above 97.5% for various oil/water mixtures. Results also demonstrate that the functionalized nylon mesh has excellent recyclability and durability in terms of oil/water separation. Additionally, polyurethane sponge slice and polyester fabric are also functionalized and employed to separate oil/water mixtures efficiently, demonstrating the wide suitability of this method. This simple, green and highly efficient method overcomes a nontrivial hurdle for environmentally-safe separation of oil/water mixtures, and offers insights into the design of advanced materials for practical oil/water separation.

The COVID-19 pandemic has brought life changing conditions to families that require coping strategies in order to survive and achieve family well-being. This study aims to analyze differences between single earner and dual earner families during the COVID-19 pandemic and to analyze the factors that influence subjective family well-being. The research design used was a cross sectional study with sample collection through non-probability sampling. Data collection was carried out by filling out questionnaires online. The number of respondents involved in the study was 2084 intact families with children residing in DKI Jakarta, West Java, and Banten Provinces. Reliability and validity tests were conducted. The results of the independent t-test showed that dual-earner families experienced better life changes and a higher level of subjective family well-being than single-earner families and had lower economic pressure and lower economic coping than single earner families. The SEM analysis found that life changes affected economic coping negatively and subjective family well-being positively. Family income influenced economic coping negatively and subjective family well-being positively. Finally, it was found that economic coping had no effect on subjective family well-being.