The best optimum temperature for the isolate was 30○C while the pH for the maximum mineral removal was 6. The best primary mineral removal was 100mg/L, while the maximum removal for all minerals was obtained after 8 hrs, and the maximum removal efficiency was obtained after 24 hrs. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/ minute. Inoculums of 5ml/ 100ml which contained 106 cell/ ml showed maximum removal for the isolate.

In this study, the behavior of square helical piles models (5×5) mm² embedded in expansive soil bed overlaying a layer of sandy soil was investigated. The sand layer 200mm thickness was compacted into four sub layers in a steel container with diameter 400mm in size. Sandy soil layer was compacted into two relative densities 40% and 80%. The bed of ثءحties 40% and 80%.The bed of o00mm in size.Sandy soil layer was compacted into two relative densities 40% and 80%.The bed of oexpansive soil 300mm thickness was compacted into six sub layers on sandy soil layer. Model tests are performed with helical pile length 350mm, 400mm and 450mm and with helix diameter 15mm and 20mm. Also, one helix and double helix were

A new set of metal complexes by the general formula [M(C)2(H2O)2]Cl2 has been prepared through the interaction of the new Ligand [N1, N4-bis(4-chlorophenyl)succinamide] (C) derived from succinyl chloride with 4-Chloroaniline with the transition metal ions Mn(II), Co(II), Ni(II), Hg(II), Cu(II) and Cd(II). Compounds diagnosed by TGA, 1 H, 13CNMR and Mass spectra (for (C)), Fourier-transform infrared and Electronic spectrum, Magnetic measurement, molar conduct, (%M, %C, %H, %N). These measurements indicate that (C) is associated with the metal ion in a bi-dentate fashion by nitrogen atoms (the amide group) and the octahedral composition of these complexes is suggested. The anti-bacterial action of the compounds towards three types of bacteria

Gundelia, a genus of flowering plants native to the Mediterranean region, particularly in Iraq, holds promise as a sustainable adsorbent for the treatment of dye-polluted water. This study explores the potential of Gundelia seeds (GS) waste as a biobased adsorbent for removing methylene blue dye from synthesized wastewater. Utilizing various analytical techniques, including scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and X-ray diffraction analysis (XRD), we assessed GS as an active adsorbent with performance comparable to fabricated and expensive composites. Key parameters such as pH (3-11), pH at the point of zero charge, temperature (298-328 K), dose (0.02-0.1 g), dye concentration (10-50 ppm), and

This study investigates the potential of biogas recovery from used engine oil (UEO) by co-digestion with animals’ manure, including cow dung (CD), poultry manure (PM), and cattle manure (CM). The experimental work was carried out in anaerobic biodigesters at mesophilic conditions (37°C). Two groups of biodigesters were prepared. Each group consisted of 4 digesters. UEO was the main component in the first group of biodigesters with and without inoculum, whereby a mix of UEO and petroleum refinery oily sludge (ROS) was the component in the second group of biodigesters. The results revealed that for UEO-based biodigesters, maximum biogas production was 0.98, 1.23, 1.93, and 0 ml/g VS from UEO±CD, UEO±CM, UEO±PM, and U

The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF