Learning from experience to improve future infrastructure public-private partnerships is a focal issue for policy makers, financiers, implementers, and private sector stakeholders. An extensive body of case studies and “lessons learned” aims to improve the likelihood of success and attempts to avoid future contract failures across sectors and geographies. This paper examines whether countries do, indeed, learn from experience to improve the probability of success of public-private partnerships at the national level. The purview of the paper is not to diagnose learning across all aspects of public-private partnerships globally, but rather to focus on whether experience has an effect on the most extreme cases of public-private partnership contract failure, premature contract cancellation. The analysis utilizes mixed-effects probit regression combined with spline models to test empirically whether general public-private partnership experience has an impact on reducing the chances of contract cancellation for future projects. The results confirm what the market intuitively knows, that is, that public-private partnership experience reduces the likelihood of contract cancellation. But the results also provide a perhaps less intuitive finding: the benefits of learning are typically concentrated in the first few public-private partnership deals. Moreover, the results show that the probability of cancellation varies across sectors and suggests the relative complexity of water public-private partnerships compared with energy and transport projects. An estimated $1.5 billion per year could have been saved with interventions and support to reduce cancellations in less experienced countries (those with fewer than 23 prior public-private partnerships).

In this study, we define the unrestricted Pell and Pell-Lucas quaternions. We give generating functions, Binet formulas and some generalizations of well-known identities such as Vajda’s, Catalan’s, Cassini’s d’Ocagne’s identities.

Dust is one of the atmospheric pollutants that have adverse environmental effects and consequences. Dust fall contains particles of 100 microns or even smaller ones, which fall from the atmosphere onto the earth surface. The aim of this study is to determine the concentration of lead in dust fall samples in order to study the pollution level of this element in Zahedan, Sistan and Baluchistan Province, Iran. Therefore, sampling was carried out using 30 marble dust collectors (MDCO) for 3 months in the spring of 2015 to investigate the quantitative variation and spatial analysis of lead content in dust fall. These dust collectors were placed at 30 stations on the building roofs with a height of approximately 1.5 meters across the city. According to the results, the mean lead concentration in the spring was 90.16 mg/kg. In addition, the zoning map of lead content shows that the lowest level of lead was measured at Imam Khomeini station while the highest amount of lead appeared in Mostafa Khomeini station.

Fe3+-doped nano-TiO2 powders were prepared by sol-gel method. The photocatalytic activity of Fe3+-doped TiO2 nanoparticles was studied by using UV lamp as light source and methylene blue as degradation target. The photocatalytic activity of Fe3+-doped TiO2 was studied by degradation of 4L methylene blue solution with initial concentration of 10mg · L - 1. The results show that the photocatalytic activity of TiO2 can be improved by the addition of Fe3+. When the molar ratio of Fe3+ is 0.5-1%, the calcination temperature is 500 ℃. The photocatalytic degradation of methylene blue is the best.

The research issue at hand pertains to the intricate mechanisms of state regulation that govern the economy of Kazakhstan, particularly in the context of the international sanctions that have been instituted by the nations comprising the Eurasian Economic Union. In order to thoroughly investigate this complex subject matter, this scholarly paper employs a variety of sophisticated methodologies grounded in bibliometric analyses of the most recent 90 academic papers that focus on the various mechanisms of state regulation pertinent to the economic landscape of Kazakhstan. As a subsequent phase in this research endeavor, the modeling of higher-order moments is undertaken with the express aim of delineating the multifaceted ramifications that stem from a singular and isolated perturbation affecting one of the key variables encapsulated within the higher-order moments model. This detailed analytical approach facilitates an in-depth exploration of both the immediate outcomes and the subsequent values of the endogenous variables that are under scrutiny. The innovative aspect of this article’s findings lies in the comprehensive analysis dedicated to the state regulation of Kazakhstan’s economy, which is significantly influenced by the international sanctions that have been imposed by member countries of the Eurasian Economic Union. The outcomes of this research provide a methodical and scientifically rigorous framework for understanding the overarching system of state regulation, which is of paramount importance for cultivating sustainable development within the socio-economic dynamics that characterize the nation of Kazakhstan.