Phytomediation is an environmentally friendly green rehabilitation technology that is often incorporated with an application to improve calcium peroxide and phytohormones required for the growth of agricultural plants with the expectation to improve the effectiveness of plant rehabilitation. This study mainly consists of two parts: (1) water culture experiment and (2) pot culture experiment. In the water culture experiment, we attempt to understand the influence of the addition of calcium peroxide, phytohormones (IAA and GA₃) and a chelating agent on the growth of sunflower plants. However, in the pot culture experiment, when hormones and the chelating agent EDTA are introduced to different plant groups at the same time, if the nutrition in the water required by plants is not available, the addition of the hormone cannot negate the toxicity caused by EDTA. In terms of calcium peroxide, due to quick release of oxygen in water, this study fails to apply calcium peroxide to the water culture experiment.

When the pot culture experiment is used to examine the influence of hormones at different concentration levels on the growth of sunflowers, GA₃ 10^-8 M is reported to have the optimal effectiveness, followed by IAA 10^-8 M; IAA 10^-12 M has the lowest effectiveness. According to an accumulation analysis of heavy metals at different levels, GA₃ concentrates in leaves to transport nutrition in soil to leaves. This results in an excellent TF value of 2.329G of GA₃ than 1.845 of the control group indicating that the addition of the hormone and chelating agent to GA₃ increases the TF value and the chelating agent is beneficial to the sunflower plant. If we examine phytoattenuation ability, the one-month experiment was divided into three stages for ten days each. The concentration level of heavy metals in the soil at each stage dropped continuously while that of the control group decreased from 31.63 mg/kg to 23.96 mg/kg, GA₃ from 32.09 mg/kg to 23.04 mg/kg and EDTA from 30.65 mg/kg to 25.93 mg/kg indicating the quickest growth period of the sunflowers from the formation of the bud to blossom. During the stage, the quick upward transportation of nutrition results in quick accumulation of heavy metals; the accumulated speed of heavy metals is found higher than that of directly planted plants. This study shows an improvement in the effectiveness of the addition of hormones on plant extraction and when rehabilitation is incorporated with sunflowers with the beginning bud formation, better treatment effectiveness can be reached.

The mining sector faces a complex dilemma as an economic development agent through social upliftment in places where mining corporations operate. Resource extraction is destructive and non-renewable, making it dirty and unsustainable. To ensure corporate sustainability, this paper examines the effects of knowledge management (KM), organizational learning (OL), and innovation capability (IC) on Indonesian coal mining’s organizational performance (OP). We used factor and path analysis to examine the relationships between the above constructs. After forming a conceptual model, principal component analysis validated the factor structure of a collection of observed variables. Path analysis examined the theories. The hypothesized framework was confirmed, indicating a positive association between constructs. However, due to mining industry peculiarities, IC does not affect organizational performance (OP). This study supports the importance of utilizing people and their relevant skills to improve operational performance. The findings have implications for managers of coal mining enterprises, as they suggest that KM and OL are critical drivers of OP. Managers should focus on creating an environment that facilitates knowledge sharing and learning, as this will help improve their organizations’ performance.

Using company size as a moderator, this article examines the MENA region’s gender balance on boards and how it influences capital structure. The study uses the Generalized Method of Moments (GMM) estimate technique to analyze data from a sample of 556 non-financial organizations across 10 MENA countries from 2010 to 2023. The results show that a lower debt ratio is connected with a higher percentage of female board members. Further steps towards debt reduction include increasing the number of independent female board members and decreasing the board’s overall size. The opposite is true for larger enterprises, more profitability, more expansion opportunities, and macroeconomic variables like inflation and GDP growth, which tend to raise the debt ratio. Capital structure decisions in the MENA area are influenced by gender diversity on boards and business characteristics. Therefore, Companies in the MENA area would do well to support initiatives that increase the representation of women on corporate boards. One way to achieve this goal is to establish gender diversity targets or launch programs to increase the number of women serving on boards of directors, particularly in positions of power.

This study examines the comparative teaching effectiveness and student satisfaction between native Japanese language teachers (NJLTs) and non-native Japanese language teachers (NNJLTs). Utilizing a sample of 740 students from various educational institutions in Japan, the research employs a quantitative design, including structured questionnaires adapted from established scales. Advanced statistical methods, including factor analysis and multiple regression, were used to analyze the data. The findings reveal no significant differences in student satisfaction and language proficiency between students taught by NJLTs and NNJLTs. Additionally, regression analysis showed that cultural relatability and empathy were not significant predictors of teaching effectiveness, suggesting that factors beyond nativeness influence student outcomes. These results challenge the native-speakerism ideology, highlighting the importance of pedagogical skills, teacher-student rapport, and effective teaching strategies. The study underscores the need for inclusive hiring practices, comprehensive teacher training programs, and collaborative teaching models that leverage the strengths of both NJLTs and NNJLTs. Implications for educational policy, curriculum design, and teacher professional development are discussed, advocating for a balanced approach that values the contributions of both native and non-native teachers. Limitations include the reliance on self-reported data and the specific cultural context of Japan. Future research should explore additional variables, employ longitudinal designs, and utilize mixed-methods approaches to provide a more nuanced understanding of language teaching effectiveness.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.