The PPP scholarly work has effectively explored the material values attached to PPPs such as efficiency of services, value for money and productivity, but little attention has been paid to procedural public values. This paper aims to address this gap by exploring how Enfidha Airport in Tunisia failed to achieve both financial and procedural values that were expected from delivering the airport via the PPP route, and what coping strategies the public and private sectors deployed to ameliorate any resultant value conflicts. Based on the analysis of Enfidha Airport, it is argued that PPP projects are likely to fail to deliver financial and procedural values when the broader institutional context is not supportive of PPP arrangements, and when political and security risks are not adequately counted for during the bidding process.

This study aims to explore the research on Chinese higher education policy from 2005 to 2024 through a bibliometric analysis. It is revealed that a continuous growth trend and sustained academic interest in this field. Mainland China leads in publication quantity, showcasing the active involvement of Chinese scholars in higher education policy research. Institutions like Peking University, the University of Hong Kong, and Beijing Normal University play significant roles in this research domain. The focus of research has shifted from student attitudes to international students, teachers, innovation models, changing demands, and urban education development, reflecting a growing emphasis on sustainability and internationalization. The study highlights the positive development trajectory of Chinese higher education policy research, with expanding research focuses and deepening concerns for sustainability and internationalization.

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.

In order to explore the influence of the ferroelectric surface on the structure and properties of semiconductor oxides, the growth of CdS nanocrystals was regulated and controlled by taking single-crystal perovskite PbTiO₃ nanosheets as the substrate through a simple hydrothermal method. Through composition design, a series of PbTiO₃-CdS nanocomposite materials with different loading concentrations were prepared, and their microstructure and photocatalytic properties were systematically analyzed. Studies show that in the prepared product, CdS nanoparticles selectively grow on the surfaces of PbTiO₃ nanosheets, and their morphology is affected by the exposed surfaces of PbTiO₃ nanosheets. There is a clear interface between the PbTiO₃ substrate and CdS nanoparticles. The concentration of the initial reactant and the time of hydrothermal reaction also significantly affect the crystal morphology of CdS. Photocatalysis studies have shown that the prepared PbTiO₃-CdS nanocomposite material has a significant degradation effect on 10 mg/L of Rhodamine B aqueous solution. The degradation efficiency rises with the increase of CdS loading concentration. When degrading 10 mg/L Rhodamine B aqueous solution, the PbTiO₃-CdS sample with a mass fraction of 3% can reach a degradation rate of 72% within 120 min.