Abstract

The hydrometallurgical method was used to platinum and palladium leaching with aqua regia solution (3HCl: HNO₃). The leaching experiments were designed to obtain the optimum conditions by using Taguchi method with 16 experiments at three different factors (time, temperature and solid to liquid ratio), and each factor has four different levels. In this study, leaching the powder sample of catalytic converter that contains platinum and palladium was conducted on the basis of the formation of chloro complexes platinum and palladium (PtCl₆^2-, PdCl₄^2-) with different concentrations in the acidic solution. The optimum condi

This study aims to apply the theory of "Text from Text and the Plus Dimension" in the analysis of the Prophetic discourse found in the section on the virtues of knowledge and scholars from Imam Sahih al-Bukhari's book. This section covers several topics, including the virtue of gathering for the sake of learning, the superiority of a scholar over a worshipper, the excellence of jurisprudence in the religion of Allah, the acquisition of knowledge through the passing away of scholars, the merit of inviting people to Allah, the continuing benefit of beneficial knowledge after a scholar's demise, the warning against seeking knowledge for purposes other than Allah, and the Prophet seeking refuge from knowledge tha

The catalytic wet air oxidation (CWAO) of phenol has been studied in a trickle bed reactor

using  active  carbon  prepared  from  date  stones  as  catalyst  by  ferric  and  zinc  chloride activation (FAC and ZAC). The activated carbons were characterized by measuring their surface area and adsorption capacity besides conventional properties, and then checked for CWAO using a trickle bed reactor operating at different conditions (i.e. pH, gas flow rate, LHSV, temperature and oxygen partial pressure). The results showed that the active carbon (FAC and ZAC), without any active metal supported, gives the highest phenol conversion. The reaction network proposed account

Due to the rapid advancement of technology and the technology of things, modern industries start to need a highprecision equipment and surface finishing, so many finishing processes began to develop. One of the modern processes is Magnetic Abrasive Finishing (MAF), which is a high-precision process for internal and external finishing under the influence of a magnetic field of abrasive particles. Boron Carbide (B4C) ceramics was tested by mixing it with iron (Fe) and produced abrasive particles to reduce the intensity of scraping on the surface, reduce the economic cost and achieve a high finishing addition to remove the edges at the same time. The material selected for the samples was mild steel (ASTM E415) under (Quantity of Abrasives, Mac

Two homopolymeric and three copolymeric additives for base oil were synthesized using octyl acrylate (OA) and tert-butyl acrylamide (TBA) monomers. The two additives named P1 and P2 are the homopolymers of TBA and OA, respectively, whereas copolymeric additives named Co1, Co2, and Co3 were synthesized by varying the ratios of TBA:OA as 1:3, 3:1 and 1:1, respectively. The prepared polymers were characterized by Fourier Transform Infrared (FTIR). Based on the solubility of synthesized polymers in base oil and reactivity ratios of TBA/OA copolymer (0.222, 0.434) calculated by Fineman-Ross method, P2, Co1, Co2 and Co3 were selected to evaluate their performance as pour point depressant (PPD), viscosity improver (VII), and anticorrosion addit

Flavonoids were extracted from Zizyphus spina-christi leaves by Ethyl acetate after acid digested and used as antioxidant. The dried extract was added separately to each sample of fat extracted from hallow cow and sheep bones as follows: T1 cow fat, T2 control for cow fat, T3 sheep fat and T4 control for sheep fat (the control T2 and T4 reffered to samples without added antioxidant).
Samples were stored at -18, 5, 25 and 55 °C for 28 days. The storage trials were conducted at -18, 5 and 25 °C for 28 days for T1, T2, T3 and T4. The chemical indices examined initially and at the end of storage period. PVs was 1.46, 1.46, 1.8 and 1.8 meq/ Kg oil respectively, FFA values were 0.245, 0.245, 0.244 and 0.244% respectively and TBA va

A field-pilot scale slow sand filter (SSF) was constructed at Al-Rustamiya Sewage Treatment Plant (STP) in Baghdad city to investigate the removal efficiency in terms of Biochemical Oxygen Demand (BOD5), Chemical oxygen demand (COD), Total Suspended Solids (TSS) and Chloride concentrations for achieving better secondary effluent quality from this treatment plant. The SSF was designed at a 0.2 m/h filtration rate with filter area 1 m2 and total filter depth of 2.3 m. A filter sand media 0.35 mm in size and 1 m depth was supported by 0.2 m layer of gravel of size 5 mm. The secondary effluent from Al-Rustamiya STP was used as the influent to the slow sand filter. The results showed that the removal of BOD5, COD, TSS, and Chloride were

Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att