The relationship between transport infrastructure and accessibility has long stood as a central research area in regional and transport economics. Often invoked by governments to justify large public spending on infrastructure, the study of this relationship has led to conflicting arguments on the role that transport plays in productivity. This paper expands the existing body of knowledge by adopting a spatial analysis (with spillover effects) that considers the physical effects of investment in terms of accessibility (using distinct metrics). The authors have used the Portuguese experience at regional level over the last 30 years as a case study. The main conclusions are as follows: i) the choice of transport variables matters when explaining productivity, and more complex accessibility indicators are more correlated with; ii) it is important to account for spill-over effects; and iii) the evidence of granger causality is not widespread but depends on the regions.

This study provides an evaluation of the environmental impact and economic benefits associated with the disposal of mango waste in Thailand, utilizing the methodologies of life cycle assessment (LCA) and cost-benefit analysis (CBA) in accordance with internationally recognized standards such as ISO 14046 and ISO 14067. The study aimed to assess the environmental impact of mango production in Thailand, with a specific focus on its contribution to global warming. This was achieved through the application of a life cycle assessment methodology, which enabled the determination of the cradle-to-grave environmental impact, including the estimation of the mango production’s global warming potential (GWP). Based on the findings of the feasibility analysis, mango production is identified as a novel opportunity for mango farmers and environmentally conscious consumers. This is due to the fact that the production of mangoes of the highest quality is associated with a carbon footprint and other environmental considerations.  Based on the life cycle assessment conducted on conventional mangoes, taking into account greenhouse gas (GHG) emissions, it has been determined that the disposal of 1 kg of mango waste per 1 rai through landfilling results in an annual emission of 8.669 tons of carbon. This conclusion is based on comprehensive data collected throughout the entire life cycle of the mangoes. Based on the available data, it can be observed that the quantity of gas released through the landfilling process of mango waste exhibits an annual increase in the absence of any intervening measures. The cost benefit analysis conducted on the life cycle assessment (LCA) of traditional mango waste has demonstrated that the potential benefits derived from its utilization are numerous. The utilization of the life cycle assessment (LCA) methodology and the adoption of a sustainable business model exemplify the potential for developing novel eco-sustainable products derived from mango waste in forthcoming time.

This paper conducts a comparative analysis of mentoring and metacognition in education, unveiling their intricate connections. Both concepts, though seemingly disparate, prove to be interdependent within the educational landscape. The analysis showcases the dynamic interplay between mentoring and metacognition, emphasizing their reciprocal influence. Metacognition, often perceived as self-awareness and introspection, is found to complement the relational and supportive nature of mentoring. Within this context, metacognitive education within mentoring emerges as a vital component. Practical recommendations are offered for effective metacognitive training, highlighting its role in enhancing cognitive and metacognitive skills. Moreover, the paper introduces the concept of a “mentoring scaffolding system.” This system emphasizes mentor-led gradual independence for mentees, facilitating their professional and personal growth. The necessity of fostering a metacognition culture in education is a central theme. Such a culture promotes improved performance and lifelong learning. The paper suggests integrating metacognition into curricula and empowering learners as essential steps toward achieving this culture. In conclusion, this paper advocates for the integration of metacognition into mentoring and education, fostering self-awareness, independence, and adaptability. These attributes are deemed crucial for individuals navigating the challenges of the information age.

This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

The present study demonstrates the fabrication of heterogeneous ternary composite photocatalysts consisting of TiO₂, kaolinite, and cement (TKCe),which is essential to overcome the practical barriers that are inherent to currently available photocatalysts. TKCe is prepared via a cost-effective method, which involves mechanical compression and thermal activation as major fabrication steps. The clay-cement ratio primarily determines TKCe mechanical strength and photocatalytic efficiency, where TKCe with the optimum clay-cement ratio, which is 1:1, results in a uniform matrix with fewer surface defects. The composites that have a clay-cement ratio below or above the optimum ratio account for comparatively low mechanical strength and photocatalytic activity due to inhomogeneous surfaces with more defects, including particle agglomeration and cracks. The TKCe mechanical strength comes mainly from clay-TiO₂ interactions and TiO₂-cement interactions. TiO₂-cement interactions result in CaTiO₃ formation, which significantly increases matrix interactions; however, the maximum composite performance is observed at the optimum titanate level; anything above or below this level deteriorates composite performance. Over 90% degradation rates are characteristic of all TKCe, which follow pseudo-first-order kinetics in methylene blue decontamination. The highest rate constant is observed with TKCe 1-1, which is 1.57 h⁻¹ and is the highest among all the binary composite photocatalysts that were fabricated previously. The TKCe 1-1 accounts for the highest mechanical strength, which is 6.97 MPa, while the lowest is observed with TKCe 3-1, indicating that the clay-cement ratio has a direct relation to composite strength. TKCe is a potential photocatalyst that can be obtained in variable sizes and shapes, complying with real industrial wastewater treatment requirements.

Implementing green retrofitting can save 50–90% of energy use in buildings built worldwide. Government policies in several developed countries have begun to increase the implementation of green retrofitting buildings in those countries, which must rise by up to 2.5% of the lifespan of buildings by 2030. By 2050, it is hoped that more than 85% of all buildings will have been retrofitted. The high costs of implementing green retrofitting amounting to 20% of the total initial construction costs, as well as the uncertainty of costs due to cost overruns are one of the main problems in achieving the implementation target in 2050. Therefore, increasing the accuracy of the costs of implementing green retrofitting is the best solution to overcome this. This research is limited to analyzing the factors that influence increasing the accuracy of green retrofitting costs based on WBS, BIM, and Information Systems. The results show that there are 10 factors affecting the cost accuracy of retrofitting or customizing high-rise office buildings, namely Energy Use Efficiency, Water Use Efficiency, Use of Environmentally Friendly Materials, Maintenance of Green Building Performance during the Use Period, Initial Survey, Project Information Documents, Cost Estimation Process, Resources, Legal, and Quantity Extraction applied. These factors are shown to increase the accuracy of green retrofitting costs.