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 the current work, it was investigated to the K X-ray fluorescence efficiency and chemical effect on vacancy transfer probability for some tin compounds. We used Br₂Tin, TinI₂, SeTin, TinF₂, TinSO₄, TinCl₂, TinO and TinS compounds for experimental study. The target samples were irradiated with ²⁴¹Am annular radioactive source at the intensity of 5 Ci which emits gamma rays at wavelength of 0.2028 nm. The characteristic x-rays emitted because of the excitation are collected by a high-resolution HPGe semiconductor detector. It has been determined that the experimental calculations of the tin (Sn) element are compatible with the theoretical calculation. In addition, we have calculated the experimental intensity ratios, fluorescence yields and total vacancy transfer probabilitiesfor other Sn compounds. 

Over the past decade, Ontario has seen a renewal in efforts to stimulate economic growth by investing in infrastructures. In this paper, we analyze the impact of public infrastructure investment on economic performance in this province. We use a multivariate dynamic time series methodological approach, based on the use of vector autoregressive models to estimate the elasticities and marginal products of six different types of public infrastructure assets on private investment, employment and output. We find that all types of public investment crowd in private investment while investment in highways, roads, and bridges crowds out employment. We also find that all types of public investment, with the exception of highways, roads and bridges, have a positive effect on output. The relatively large range of results estimated for the impact of each of the different public infrastructure types suggests that a targeted approach to the design of infrastructure investment policy is required. Infrastructure investment in transit systems and health facilities display the highest returns for output and the largest effects on employment and labor productivity. In terms of the nature of the empirical results presented here it would be important to highlight the fact that investments in health infrastructures as well as investments in education infrastructures are of great relevance. This is a pattern consistent with the mounting international evidence on the importance of human capital for long term economic performance.

The size effect on the free vibration and bending of a curved FG micro/nanobeam is studied in this paper. Using the Hamilton principle the differential equations and boundary conditions is derived for a nonlocal Euler-Bernoulli curved micro/nanobeam.  The material properties vary through radius direction. Using the Navier approach an analytical solution for simply supported boundary conditions is obtained where the power index law of FGM, the curved micro/nanobeam opening angle, the effect of aspect ratio and nonlocal parameter on natural frequencies and the radial and tangential displacements were analyzed. It is concluded that increasing the curved micro/nanobeam opening angle results in decreasing and increasing the frequencies and displacements, respectively. To validate the natural frequencies of curved nanobeam, when the radius of it approaches to infinity, is compared with a straight FG nanobeam and showed a good agreement.

In this study, the effect of roasting and boiling on the yield and oxidative stability of soya bean oil was investigated. The oil was soxhlet extracted and the oxidative stability was determined by the free fatty acid value, acid value and peroxide value. The results showed that the oil yield, free fatty acid value, acid value and peroxide value were significantly affected by roasting, boiling, and the thermal treatment time. The percentage oil yield in the control oil sample was 18.51%, which increased to 20.24% and 20.73% after boiling and roasting respectively, at 40mins. The corresponding free fatty acid and the peroxide value of the control oil sample were 0.14% and 2.04 meqO₂/kg, which increased to 0.82% and 6.60 meqO₂/kg by roasting, and 0.47% and 5.62 meqO₂/kg by boiling respectively. Thus the oil yield, free fatty acid value, peroxide value, and acid value increased with increasing roasting and boiling time.
The results indicate that roasting provides a higher oil yield than boiling, but boiled oil has higher oxidative stability than roasted oil.

By reviewing US state-level panel data on infrastructure spending and on per capita income inequality from 1950 to 2010, this paper sets out to test whether an empirical link exists between infrastructure and inequality. Panel regressions with fixed effects show that an increase in the growth rate of spending on highways and higher education in a given decade correlates negatively with Gini indices at the end of the decade, thus suggesting a causal effect from growth in infrastructure spending to a reduction in inequality through better access to education and opportunities for employment. More significantly, this relationship is more pronounced with inequality at the bottom 40 percent of the income distribution. In addition, infrastructure expenditures on highways are shown to be more effective at reducing inequality. By carrying out a counterfactual experiment, the results show that those US states with a significantly higher bottom Gini coefficient in 2010 had underinvested in infrastructure during the previous decade. From a policy-making perspective, new innovations in finance for infrastructure investments are developed, for the US, other industrially advanced countries and also for developing economies.