Public-private partnerships (PPPs) were established in Brazil at the beginning of this century, following a global trend of using these partnerships to stimulate investment in infrastructures, particularly in a framework of restrictive budgetary and fiscal conditions. Despite their growing importance and the expectation of an expanding role in the future, not much is known about the actual facts on the ground. The objective of this paper is to be a first step in the direction of filling this information gap by providing important stylized facts about the universe of PPPs in Brazil: the quantitative evolution of PPP adoptions; the characterization of the geographical distribution of PPPs by government level (federal, state, district, and municipal); the characterization of the PPP intervention areas, including the total value of contracts and the modalities of PPP concession (sponsored and administrative). This objective is rendered possible by the development of a new database that covers the entire process of PPP contracting from 2005 to 2022, including the opening of public consultation procedures, the publication of the official notice, and the signing of contracts, as well as multiple thematic, financial, jurisdictional, and regional indicators. In turn, we see the establishment of these stylized facts as a necessary first step in the direction of understanding the factors that may determine or condition their adoption. In general, having a clear picture of the universe of the PPPs in Brazil is fundamental as their use and their role are expected to significantly increase in the future as the country pursues a path of improved economic activity and well-being of the population.

In this study, the effect of porogenic solvents on pore size distribution of the polycaprolactone (PCL) thin films was investigated. Five thin PCL films were prepared using the solvent-casting method. Chloroform, Methylene Chloride (MC) and three different compositions of MC/ Dimethylformamide (DMF) (80/20, 50/50 and 20/80) were used as solvents. Scanning Electron Microscopy (SEM) investigations were employed to study morphology and consequently the pore size distribution of the prepared films. The PCL films made by chloroform and MC as a solvent were completely non-porous. Whereas the other films (made by a combination of MC and DMF) showed both uni-modal and bi-modal pore size distributions.

This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

Census 2022 of Saudi Arabia was released recently, with 12 years of intercensal interval. Although it appeared provisional having no reports similar to the 2010 census, efforts to analyze, interpret, disseminate, and discuss were essential for building structures and systems at par with demographic trends and patterns. An analysis was carried out with this census data compared to 2004 and 2010 to track population change—demographic pace, trends, and patterns—over the two decades. Data from all three censuses were analyzed with conventional demographic techniques. A reduction in growth was observed with a declining percentage of the childhood population but with an expanding percentage of the adults (working age) indicating a demographic dividend resulted, mostly, from fertility decline. An aging trend established by the previous censuses was lost, recently: the constriction of the pyramid of 2010 was changed to a different shape. Not only the percentage distribution trends were uneven but also the age-based indices. Thus, these trends revealed a demographic difference to an extent, that demands standardized reports, uniform procedures for the data collection and compilation, and geographic distribution equations. The increasing concentration in urban centers of major administrative areas—Al-Riyadh, Makkah Al-Mokarramah, and the Eastern Region demand redistribution policies. Self-contained townships appear as a strategic option in population redistribution, guaranteeing quality standards and lifestyle.

The smallest administrative unit of the sixth national census-township (town) is selected as the basic unit, the population spatial distribution characteristics at the township (town) level in karst mountainous areas of northwest Guangxi are analyzed by using Lorenz curve and spatial correlation analysis method, and the influence intensity of natural factors on regional population spatial distribution is detected by using geographic detector method. The results show that: 1. the spatial distribution of population at the township (town) level has the characteristics of imbalance, showing generally significant positive correlation and certain aggregation; 2. There are significant differences in the impact of the spatial distribution of various natural factors on the population distribution. For the towns without karst distribution in the northwest and central south of the study area, the population density increases with the increase of factors conducive to human residence, but the average population density is only 79 people/km². In the towns with karst distribution in the East and south, the spatial distribution of population density and natural factors is not a simple increase or decrease relationship, but fluctuates with the change of karst distribution area. 3. The factor detection results of the geographic detector show that the altitude has the greatest impact on the spatial distribution of population. The interactive detection results show that the impact intensity of any two natural factors after superposition and interaction presents nonlinear enhancement and two factor enhancement. It can be seen that the karst mountain area in northwest Guangxi is similar to other areas. Altitude is one of the main factors affecting the spatial distribution of population, but the river network density and unique geological landform of karst mountain area have a strong catalytic effect on the spatial distribution of population. The superposition and interaction with other factors can further strengthen the impact on population distribution.