The China-Pakistan Economic Corridor (CPEC) has been one of the most prominent components of the Belt and Road Initiative (BRI). Most of the discussion on CPEC has centered around the macroeconomic effects on the economy. However, research on the fine details of CPEC’s financing structure has not been conducted. This paper aims to fill the gap by providing a detailed description of the financing of CPEC and how the money maps on to different sectors of the Pakistani economy. We also discuss some macroeconomic concerns and ways to mitigate these risks.

An investigation is conducted into how radiation affects the non-Newtonian second-grade fluid in double-diffusive convection over a stretching sheet. When fluid is flowing through a porous material, the Lorentz force and viscous dissipation are also taken into account. The flow equations are coupled partial differential equations that can be solved by MATLAB’s built-in bvp4c algorithm after being transformed into ODEs using appropriate similarity transformations. Utilizing graphs and tables, the impact of a flow parameter on a fluid is displayed. On velocity, temperature, and concentration profiles, the effects of the magnetic field, Eckert number, and Schmidt number have been visually represented. Calculate their inaccuracy by comparing the Nusselt number and Sherwood number values to those from earlier investigations.

Fire, a phenomenon occurs in most parts of the world and causes severe financial losses, even, irreparable damages. Many parameters are involved in the occurrence of a fire; some of which are constant over time (at least in a fire cycle), but the others are dynamic and vary over time. Unlike the earthquake, the disturbance of fire depends on a set of physical, chemical, and biological relations. Monitoring the changes to predict the occurrence of fire is efficient in forest management. Method: In this research, the Persian and English databases were structurally searched using the keywords of fire risk modeling, fire risk, fire risk prediction, remote sensing and the reviewed papers that predicted the fire risk in the field of remote sensing and geographic information system were retrieved. Then, the modeling and zoning data of fire risk prediction were extracted and analyzed in a descriptive manner. Accordingly, the study was conducted in 1995-2017. Findings: Fuzzy analytic hierarchy process (AHP) zoning method was more practical among the applied methods and the plant moisture stress measurement was the most efficient among the remote sensing indices. Discussion and Conclusion: The findings indicate that RS and GIS are effective tools in the study of fire risk prediction.

As an important ecosystem type in the coastal zone, mangroves have important ecological functions, such as maintaining coastal biodiversity, preventing wind and consolidating the coast, promoting silt and building land. It is of great significance to understand the protected status of mangroves in the context of climate change and rapid urbanization. Based on the mangrove classification data from remote sensing interpretation, through vacancy analysis, the in-situ protection status of mangroves in China is analyzed. The results show that the total area of mangroves distributed in China is 264 km² (excluding the statistical data of Hong Kong, Macao and Taiwan), of which 61.4% are protected in natural reserves. In terms of the main provinces where mangroves are distributed, the mangrove area distributed in Hainan Province is small but the protection proportion is high, while the mangrove area distributed in Guangxi and Guangdong Province is large but the proportion of protected areas is relatively low. Among the three mangrove types, Rhizophora apiculate-Xylocarpus granatum and Rhizophora stylosa-Bruguiera gymnorrhiza had high proportions (>90%) covered by reserves, but relatively small areas. In contrast, Kandelia candel-Aegiceras corniculatum-Avicennia marina had relatively low reserve coverage (52.6%), but a large area. The study puts forward the key areas of mangrove distribution outside the nature reserve, and suggests that they should be protected by delimiting ecological protection red lines.

Starting from the ‘90s, there has been a significant increase in PPP use in the public sector in Europe, benefiting the implementation of infrastructure projects. In Italy, PPP is still much more limited than in such countries as the UK and France: the projects funded are smaller and the sectors involved are less appropriate. Based on the economic literature, European initiatives and international comparisons, the paper examines aspects of regulations that could encourage the appropriate use of PPP and considers the problems with the Italian regulations, while proposing some corrective measures. The main limitations involve: i) the absence of adequate preliminary assessments about the advantages of using PPP rather than the traditional procurement, ii) the relative lack of attention to the contract terms, iii) inadequate safeguards to ensure the bankability of the projects, and iv) limited information transparency and accessibility.

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.