The last decades have offered new challenges to researchers worldwide through the problems our planet is facing both in the environment protection field and the need to replace fossil fuels with new environmentally friendly alternatives. Bioenergy as a form of renewable energy is an acceptable option from all points of view and biofuels due to their biological origin have the ability to satisfy the new needs of humanity. By releasing some non-polluting combustion products into the atmosphere, biofuels have already been adopted as additives in traditional liquid fuels, being intended mainly for internal combustion engines of automobiles. The current work proposes an extension of biofuels application in combustion processes specific to industrial furnaces. This technical concern is not found in the literature, except for achievements of the research team involved in this work, which has performed previous investigations. A 51.5 kW-burner was designed to operate with glycerine originating from triglycerides of plants and animals, mixed with ethanol, an alcohol produced by the chemical industry recently used as an additive in gasoline for automobile engines. Industrial oxygen was chosen as the oxidizing agent necessary for the liquid mixture combustion, allowing to obtain much higher flame temperatures compared to the usual combustion processes using air. Mixing glycerine with ethanol in 8.8 ratio allowed growing flame stability, accentuated also by creating swirl currents in the flame through the speed regime of fluids at the exit from the burner body. Results were excellent both through the flame stability and low level of polluting emissions.

Global warming is a thermodynamic problem. When excess heat is added to the climate system, the land warms more quickly than the oceans due to the land’s reduced heat capacity. The oceans have a greater heat capacity because of their higher specific heat and the heat mixing in the upper layer of the ocean. Thermodynamic Geoengineering (TG) is a global cooling method that, when deployed at scale, would generate 1.6 times the world’s current supply of primary energy and remove carbon dioxide (CO₂) from the atmosphere. The cooling would mirror the ostensible 2008–2013 global warming hiatus. At scale, 31,000 1-gigawatt (GW) ocean thermal energy conversion (OTEC) plants are estimated to be able to: a) displace about 0.8 watts per square meter (W/m²) of average global surface heat from the surface of the ocean to deep water that could be recycled in 226-year cycles, b) produce 31 terawatts (TW) (relative to 2019 global use of 19.2 TW); c) absorb about 4.3 Gt CO₂ per year from the atmosphere by cooling the surface. The estimated cost of these plants is $2.1 trillion per year, or 30 years to ramp up to 31,000 plants, which are replaced as needed thereafter. For example, the cost of world oil consumption in 2019 was $2.3 trillion for 11.6 TW. The cost of the energy generated is estimated at $0.008/KWh.

One functional class is described in terms of one-sided modulus of continuity and the modulus of positive (negative) variation on which there
is a uniform convergence of the truncated cardinal Whittaker functions.

The Consumer Price Index (CPI) is a vital gauge of economic performance, reflecting fluctuations in the costs of goods, services, and other commodities essential to consumers. It is a cornerstone measure used to evaluate inflationary trends within an economy. In Saudi Arabia, forecasting the Consumer Price Index (CPI) relies on analyzing CPI data from 2013 to 2020, structured as an annual time series. Through rigorous analysis, the SARMA (0,1,0) (12,0,12) model emerges as the most suitable approach for estimating this dataset. Notably, this model stands out for its ability to accurately capture seasonal variations and autocorrelation patterns inherent in the CPI data. An advantageous feature of the chosen SARMA model is its self-sufficiency, eliminating the need for supplementary models to address outliers or disruptions in the data. Moreover, the residuals produced by the model adhere closely to the fundamental assumptions of least squares principles, underscoring the precision of the estimation process. The fitted SARMA model demonstrates stability, exhibiting minimal deviations from expected trends. This stability enhances its utility in estimating the average prices of goods and services, thus providing valuable insights for policymakers and stakeholders. Utilizing the SARMA (0,1,0) (12,0,12) model enables the projection of future values of the Consumer Price Index (CPI) in Saudi Arabia for the period from June 2020 to June 2021. The model forecasts a consistent upward trajectory in monthly CPI values, reflecting ongoing economic inflationary pressures. In summary, the findings underscore the efficacy of the SARMA model in predicting CPI trends in Saudi Arabia. This model is a valuable tool for policymakers, enabling informed decision-making in response to evolving economic dynamics and facilitating effective policies to address inflationary challenges.

Attempts were made in the present study to design and develop skeletally modified ether linked tetraglycidyl epoxy resin (TGBAPSB), which is subsequently reinforced with different weight percentages of amine functionalized mullite fiber (F-MF). The F-MF was synthesized by reacting mullite fiber with 3-aminopropyltriethoxysilane (APTES) as coupling agent and the F-MF structure was confirmed by FT-IR. TGBAPSB reinforced with F-MF formulation was cured with 4,4’-diamino diphenyl methane (DDM) to obtain nanocomposite. The surface morphology of TGBAPSB-F-MF epoxy nanocomposites was investigated by XRD, SEM and AFM studies. From the study, it follows that these nanocomposite materials offer enhancement in mechanical, thermal, thermo-mechanical, dielectric properties compared to neat (TGBAPSB) epoxy matrix. Hence we recommend these nanocomposites for a possible use in advanced engineering applications that require both toughness and stiffness.