The effects of three kinds of oxygenated fuel blends—i.e., ethanol-gasoline, n-butanol-gasoline, and 2,5-dimethylfuran (DMF)-gasoline-on fuel consumption, emissions, and acceleration performance were investigated in a passenger car with a chassis dynamometer. The engine mounted in the vehicle was a four-cylinder, four-stroke, turbocharging gasoline direct injection (GDI) engine with a displacement of 1.395 L. The test fuels include ethanol-gasoline, n-butanol-gasoline, and DMF-gasoline with four blending ratios of 20%, 50%, 75%, and 100%, and pure gasoline was also tested for comparison. The original contribution of this article is to systemically study the steady-state, transient-state, cold-start, and acceleration performance of the tested fuels under a wide range of blending ratios, especially at high blending ratios. It provides new insight and knowledge of the emission alleviation technique in terms of tailoring the biofuels in GDI turbocharged engines. The results of our works showed that operation with ethanol–gasoline, n-butanol–gasoline, and DMF–gasoline at high blending ratios could be realized in the GDI vehicle without any modification to its engine and the control system at the steady state. At steady-state operation, as compared with pure gasoline, the results indicated that blending n-butanol could reduce CO2, CO, total hydrocarbon (THC), and NOX emissions, which were also decreased by employing a higher blending ratio of n-butanol. However, a high fraction of n-butanol increased the volumetric fuel consumption, and so did the DMF–gasoline and ethanol–gasoline blends. A large fraction of DMF reduced THC emissions, but increased CO2 and NOX emissions. Blending n-butanol can improve the equivalent fuel consumption. Moreover, the particle number (PN) emissions were significantly decreased when using the high blending ratios of the three kinds of oxygenated fuels. According to the results of the New European Drive Cycle (NEDC) cycle, blending 20% of n-butanol with gasoline decreased CO2 emissions by 5.7% compared with pure gasoline and simultaneously reduced CO, THC, NOX emissions, while blending ethanol only reduced NOX emissions. PN and particulate matter (PM) emissions decreased significantly in all stages of the NEDC cycle with the oxygenated fuel blends; the highest reduction ratio in PN was 72.87% upon blending 20% ethanol at the NEDC cycle. The high proportion of n-butanol and DMF improved the acceleration performance of the vehicle.

No abstract

<abstract> <p>Unlike prior solvency prediction studies conducted in Egypt, this study aims to set up a real picture of companies' financial performance in the Egyptian insurance market. Therefore, 11 financial ratios commonly used by NAIC, AM BEST Company, and S &amp; P Global Ratings were calculated for all property-liability insurance companies in Egypt from 2010 to 2020. They have been used to measure those companies' financial performance efficiency levels by comparing these ratios with the international standard limits. The financial analysis results for those companies revealed that property-liability insurers in Egypt do not have the same level of financial performance efficiency where those companies are classified into three groups: excellent, good, and poor. Furthermore, this paper investigates using the stepwise logistic regression model to determine the most factors among these selected financial ratios that influence those companies' financial performance. The results suggest that only three ratios were statistically significant predictors: "Risk retention rate", "Insurance account receivable to total assets", and "Net profit after tax to total assets". Finally, this paper presents the multi-layers artificial neural network with a backpropagation algorithm as a new solvency prediction model with perfect classifying accuracy of 100%. The trained ANN could predict the next fiscal year with a prediction accuracy of 91.67%, and this percent is a good and favorable result comparing to other solvency prediction models used in Egypt.</p> </abstract>

The article is devoted to the current topic of today - politics and the economy of China with the countries of Central Asia. The paper poses the problems of China’s interests in Central Asia, as well as the prospects for cooperation between these countries. China's role in development of the modern economy is steadily increasing, and therefore the vector investment cooperation with this country is one of fundamental for the countries of Central Asia, which, in addition, are neighbors of China. For China, which has a very limited stock of natural resources, countries rich in oil, gas, and other resources become of strategic importance. The purpose of the study is to identify the results of a comparative analysis of the main interests of the PRC in the Central Asian region, namely in Kazakhstan and to determine the effect of three economic data on Chinese direct investment. To achieve this goal, the ''Kao Residual Cointegration Test'' and the “Pooled Least Squares" method were used. The research work is using the EViews software and the Pool Least Squares method. The main results were identified and shown in schematic form. The interests and volume of investments of the People’s Republic of China in Central Asia were identified in this area. The article has practical value and can be offered for reading to a different target audience.