Biomass is a popular renewable carbon source because it has a lot of potential as a substitute for scarce fossil fuels and has been used to make essential compounds like 5-hydroxymethylfurfural (HMF). One of the main components of biomass, glucose, has been extensively studied as a precursor for the production of HMF. Several efforts have been made to find efficient and repeatable procedures for the synthesis of HMF, a chemical platform used in the manufacturing of fuels and other high-value compounds. Sulfonated graphite (SG) was produced from spent dry batteries and utilized as a catalyst to convert glucose to 5-hydroxymethylfurfural (HMF). Temperature, reaction time, and catalyst loading were the variables studied. When dimethyl sulfo

Parasitic diseases can affect infection with COVID-19 obviously, as protective agents, or by reducing severity of this viral infection. This current review mentions the common symptoms between human parasites and symptoms of COVID-19, and explains the mechanism actions of parasites, which may prevent or reduce severity of this viral infection. Pre-existing parasitic infections provide prohibition against pathogenicity of COVID-19, by altering the balance of gut microbiota that can vary the immune response to this virus infection.  

For more than a decade, externally bonded carbon fiber reinforced polymer (CFRP) composites successfully utilized in retrofitting reinforced concrete structural elements. The function of CFRP reinforcement in increasing the ductility of reinforced concrete (RC) beam is essential in such members. Flexural and shear behaviors, ductility, and confinement were the main studied properties that used the CFRP as a strengthening material. However, limited attention has been paid to investigate the energy absorption of torsion strengthening of concrete members, especially two-span concrete beams. Hence, the target of this work is to investigate the effectiveness of CFRP-strengthening technique with regard to energy absorption of two-span RC

Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

The effect of three ionic liquids viz., 1-hexyl-3-methylimidazolium tetrafluoroborate (ILE), 1-hexyl-3-metylimidazolium hexafluorophosphate (ILF) and 1-octyl-3-methylimidazolium tetrafluoroborate (ILG) when used as surfactants on the performance of dissolved air floatation (DAF) was investigated.

   Experiments were conducted at a temperature of 30-35 ºC, 10ppm ferric chloride as coagulant, 50% recycle ratio, pH 8, and 10 minutes treatment time  to find oil and grease (OG) and turbidity removal efficiencies at saturation pressure (2-6) bar.

ILs were used at concentration of 50 µl/liter of treated water in two positions in DAF system; the saturation vessel and the treatment tank. The performance using ILs

The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a