The climate has changed significantly under the influence of human behavior. And first of all, this is due to the change in the proportionality and concentration of greenhouse gases in the atmosphere (water vapor, carbon dioxide, methane, ozone, PFC (perfluorocarbons). This paper analyzes the dynamics of greenhouse gas emissions. Climate change has many consequences on human health throughout the world, especially in African countries. The growth of greenhouse gas emissions is viewed as a cause of infectious and non-infectious diseases, negative effects on nutrition, water security and other social disruptions. The global average temperature gradually increases, and the atmospheric CO2 concentration has exceeded 400 ppm due to the intensification of greenhouse effect. The method of energy balance was featured to simulate the trends in Greenhouse Gas Emission Forecast in different sectors until 2030. Through sensitivity analysis, we found that the reduction of anthropogenic CO2 emissions from people (cars and households) would deescalate the consequences of the above trends. Emissions are mostly associated with industries, which can be reduced if local Government will want to achieve the Paris Agreement goal.

Along with industrialization and rapid urbanization, environmental remediation is globally a perpetual concept to deliver a sustainable environment. Various organic and inorganic wastes from industries and domestic homes are released into water systems. These wastes carry contaminants with detrimental effects on the environment. Consequently, there is an urgent need for an appropriate wastewater treatment technology for the effective decontamination of our water systems. One promising approach is employing nanoparticles of metal oxides as photocatalysts for the degradation of these water pollutants. Transition metal oxides and their composites exhibit excellent photocatalytic activities and along show favorable characteristics like non-toxicity and stability that also make them useful in a wide range of applications. This study discusses some characteristics of metal oxides and briefly outlined their various applications. It focuses on the metal oxides TiO2, ZnO, WO3, CuO, and Cu2O, which are the most common and recognized to be cost-effective, stable, efficient, and most of all, environmentally friendly for a sustainable approach for environmental remediation. Meanwhile, this study highlights the photocatalytic activities of these metal oxides, recent developments, challenges, and modifications made on these metal oxides to overcome their limitations and maximize their performance in the photodegradation of pollutants.

The paper proposes a machine-learning approach to predict oil price. Market participants can forecast prices using such factors as: US key rate, US dollar index, S and P500 index, Volatility index, US consumer price index. After analyzing the results and comparing the accuracy of the model first, we can conclude that oil prices in 2019-2022 will have a slight upward trend and will generally be stable. At the time of the fall in June 2012 the price of Brent fell to a minimum of 17 months. The reason for this was the weak demand for oil futures, which was caused by poor data on the state of the US labor market.

The paper is devoted to modelling the corruption perception index in panel data framework. As corruption index is bounded from below and above, traditional econometric multiple regression will produce a bad quality model. In order to correct that, we propose a mathematical framework for modelling bounded variables implementing a logistic function. It is shown that corruption is best explained by GDP per capita and all other major macroeconomic indicators cannot add any statistically significant improvement to the models' accuracy. Thus, we assume, that society wealthiness facilitates the reduction of corruption acts. Indeed, if some individual lives in a society that does not experiences almost any shortage of resources of whatever kind, the less interested this person is in getting wealthier by applying some corruption schemes. These methods are rather popular in less wealthy countries, where temptation to engage into corruption is higher, since it can drastically increase individual's utility function. Therefore, in this research we assert, that the growth of wealth in a society makes corruption recede and not the other way around (reducing corruption helps increase GDP per capita). However, the most counterintuitive finding of this research is the fact, that GDP per capita, adjusted by purchasing power parity, produces the model of a worse quality then just using plain GDP per capita. This fact can be tentatively explained by the flaws in the methodology of calculating these adjustments, since the basket of goods varies drastically across the countries.

Quality-of-service (QoS) is the term used to evaluate the overall performance of a service. In healthcare applications, efficient computation of QoS is one of the mandatory requirements during the processing of medical records through smart measurement methods. Medical services often involve the transmission of demanding information. Thus, there are stringent requirements for secure, intelligent, public-network quality-of-service. This paper contributes to three different aspects. First, we propose a novel metaheuristic approach for medical cost-efficient task schedules, where an intelligent scheduler manages the tasks, such as the rate of service schedule, and lists items utilized by users during the data processing and computation through the fog node. Second, the QoS efficient-computation algorithm, which effectively monitors performance according to the indicator (parameter) with the analysis mechanism of quality-of-experience (QoE), has been developed. Third, a framework of blockchain-distributed technology-enabled QoS (QoS-ledger) computation in healthcare applications is proposed in a permissionless public peer-to-peer (P2P) network, which stores medical processed information in a distributed ledger. We have designed and deployed smart contracts for secure medical-data transmission and processing in serverless peering networks and handled overall node-protected interactions and preserved logs in a blockchain distributed ledger. The simulation result shows that QoS is computed on the blockchain public network with transmission power = average of −10 to −17 dBm, jitter = 34 ms, delay = average of 87 to 95 ms, throughput = 185 bytes, duty cycle = 8%, route of delivery and response back variable. Thus, the proposed QoS-ledger is a potential candidate for the computation of quality-of-service that is not limited to e-healthcare distributed applications.