A novel metal-organic framework (MOF) sorbent based on tannic acid/copper (TA/Cu) was synthesized and characterized for the application of the anticancer drug imatinib (IMA) from biological samples. The TA/Cu MOF was prepared via a facile coordination reaction and thoroughly characterized by SEM, XRD, and FTIR techniques. Critical parameters influencing the extraction efficiency of imatinib mesylate (IMAM), including pH, ionic strength, desorption solvent, and adsorption-desorption time were optimized. With acetonitrile as the desorption solvent, the method demonstrated a broad linear range of 0.55-300 μg L-1 under ideal conditions. Limits of detection and quantification were found to be 0.16 μg L-1 and 0.55 μg L-1, respectively.

A single step extraction-cleanup procedure using porous membrane-protected micro-solid phase extraction (μ-SPE) in conjunction with liquid chromatography–tandem mass spectrometry for the extraction and determination of aflatoxins (AFs) B1, B2, G1 and G2 from food was successfully developed. After the extraction, AFs were desorbed from the μ-SPE device by ultrasonication using acetonitrile. The optimum extraction conditions were: sorbent material, C8; sorbent mass, 20 mg; extraction time, 90 min; stirring speed, 1000 rpm; sample volume, 10 mL; desorption solvent, acetonitrile; solvent volume, 350 μL and ultrasonication period, 25 min without salt addition. Under the optimum conditions, enrichment factor of 11, 9, 9 and 10 for AFG2, AFG1

The research aims to derive the efficient industrial plans for Al – shaheed public company under risk by using Target MOTAD as a linear alternative  model for the quadratic programming models.

The results showed that there had been a sort of (trade- off) between risk and the expected gross margins. And if the studied company strives to get high gross margin, it should tolerate risk and vice versa. So the management  of Al- Shaheed Company to be invited to apply the suitable procedures in the production process, in order to get efficient plans that improves it's  performance .

Gas compressibility factor or z-factor plays an important role in many engineering applications related to oil and gas exploration and production, such as gas production, gas metering, pipeline design, estimation of gas initially in place (GIIP), and ultimate recovery (UR) of gas from a reservoir. There are many z-factor correlations which are either derived from Equation of State or empirically based on certain observation through regression analysis. However, the results of the z-factor obtained from different correlations have high level of variance for the same gas sample under the same pressure and temperature. It is quite challenging to determine the most accurate correlation which provides accurate estimate for a range of pressures,

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

     This work includes the synthesis of new ester compounds containing two 1,3,4-oxadiazole rings, 15a-c and 16a-c. This was done over seven steps, starting with p-acetamido-phenol 1 and 2-mercaptobenzoimidazole 2. The structure of the products was determined using FT-IR, 1H NMR, and mass spectroscopy. The evaluation of the antimicrobial activities of some prepared compounds was achieved against four types of bacteria (two types of gram-positive bacteria; Staphylococcus aureus and Bacillus subtilis, and two types of gram-negative bacteria, Pseudomonas aeruginosa and E. Coli), as well as against one types of fungus (C. albino). The results show moderate activit against the study bacteria, and the theoretical analysis of the toxi

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

A high-performance liquid chromatography method was employed for the quantitative determination of ascorbic acid (AA) which called vitamin C in three types of Iraqi citrus (orange mandarin and aurantium ) and to establish this goal , evaluation of ascorbic acid degradation is so important due to its significant criticality when exposure to ordinary atmospheric conditions. The chromatographic analysis of AA was carried out after their sequential elution with KH2PO4 ( as mobile phase) by reverse-phase HPLC technique with C8 column and UV detection at 214 nm. .Bad resolutions was appeared clearly for C8 column , so another alternative condition were carried out to improve the resolution by replacement of C8 by C18 column .Statistical treat

In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

The - mixing ratios of -transitions from levels in populated in the reactions are calculated in present work using - ratio, constant statisticalTensor and least squares fitting methods The results obtained are in general, in good agreement or consistent, within the associated uncertainties, with these reported in Ref.[9],the discrepancies that occurs are due to inaccuracy existing in the experimental data The results obtained in the present work confirm the –method for mixed transitions better than that for pure transition because this method depends only on the experimental data where the second method depends on the pure or those considered to be pure -transitions, the same results occur in – method