In the present study, advanced oxidation treatment, the TiO₂ /UV/H₂O₂  process was applied to decolorisation of the reactive yellow dyes in aqueous solution. The UV radiation was carried out with a 6 W low-pressure mercury lamp. The rate of color removal was studied by measuring the absorbency at a characteristic wavelength. The effects of H2O2 dosage, dye initial concentration and pH on decolorisation kinetics in the batch photoreactor were investigated. The highest decolorisation rates were observed (98.8) at pH range between 3 and 7. The optimal levels of H₂O₂ needed for the process were examined. It appears that high levels of H₂O₂ could reduce decolori

Environmental pollution is regarded as a major problem, and traditional strategies such as chemical or physical remediation are not sufficient to overcome the problems of pollution. Petroleum-contaminated soil results in ecological problems, representing a danger to human health. Bioremediation has received remarkable attention, and it is a procedure that uses a biological agent to remove toxic waste from contaminated soil. This approach is easy to handle, inexpensive, and environmentally friendly; its results are highly satisfactory. Bioremediation is a biodegradation process in which the organic contaminants are completely mineralized to inorganic compounds, carbon dioxide, and water. This review discusses the bioremediation of petroleum-

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

This study concerns the removal of a trihydrate antibiotic (Amoxicillin) from synthetically contaminated water by adsorption on modified bentonite. The bentonite was modified using hexadecyl trimethyl ammonium bromide (HTAB), which turned it from a hydrophilic to a hydrophobic material. The effects of different parameters were studied in batch experiments. These parameters were contact time, solution pH, agitation speed, initial concentration (C0) of the contaminant, and adsorbent dosage. Maximum removal of amoxicillin (93 %) was achieved at contact time = 240 min, pH = 10, agitation speed = 200 rpm, initial concentration = 30 ppm, and adsorbent dosage = 3 g bentonite per 1L of pollutant solution. The characterization of the adsorbent, modi

Mefenamic acid belongs to non-steroidal anti-inflammatory drugs that are used widely for the treatment of analgesia. Our aim from this study is to establish a new assay for the quantitative determination of mefenamic acid (MFA) in the pharmaceutical sample by two sensitive and rapid flow injection-fluorometric methods. A homemade fluorometer was used in fluorescence measurements, which using solid-state laser diode 405 and 532 nm as a source, combined with a continuous flow injection technique. The first method depends on the effect of MFA on calcein blue (CLB) fluorescence at 405 nm. Another method is a study of rhodamine-6G (Rh-6G) fluorescence after adding MFA, and recording at 532 nm. Optimum parameters as fluorescent dye concen

Although G6PD deficiency is the most common genetically determined blood disorder among Iraqis, its molecular basis has only recently been studied among the Kurds in North Iraq, while studies focusing on Arabs in other parts of Iraq are still absent.

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R