A quantitative structure–retention relationship (QSRR), was developed using the genetic algorithm-partial least square (GA-PLS), Kernel partial least square (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) approach for the prediction of the retention time (RT) of doping agents in urine. These retention times are obtained by ultra-high-pressure liquid chromatography–quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). A suitable set of the molecular descriptors was calculated and the important descriptors were selected with the aid of the GA-PLS and GA-KPLS. By comparing the results, GA-KPLS descriptors are selected for L-M ANN. Finally a model with a low prediction error and a good correlation coefficient was obtained by L-M ANN. This model was used for the prediction of the RT values of some of doping agents which were not used in the modeling procedure. This is the first research on the QSRR of doping agents against the RT using the GA-PLS, GA-KPLS and L-M ANN model.

Benzamide/ Sulfuryl Chloride (SO2Cl2) reagent has been developed as a Vilsmeier- Haack(VH) reagent for benzoylation of aromatic compounds under conventional and ultrasonic sonication (US) and microwave (MW) conditions. Benzoylation is much more competent and faster than analogous VH ((Benzamide/ POCl3) or (Benzamide/SOCl2)) reagents and afforded benzoyl derivatives in fairly good yields. Reaction times are moderately less than those observed with [Benzamide/ POCl3] and (Benzamide/SOCl2) reagents. Reaction times are far less in microwave assisted (MWAR) reactions than ultrasonically assisted (USAS) reactions , which in turn are less than the conventional method with a decreasing trend: MWAR (seconds) << Sonication (minutes) << conventional (hrs). Highly remarkable rate accelerations in MW assisted reactions are attributed to bulk activation of molecules, while US assisted reactions could be accounted for cavitation effects.

In recent years, it has been noted that the silicon analogs of compounds have more pharmaceutical applications because of their more lipophilicity properties. The present research paper studies the structural and spectral properties and reactivity of the silicon analogs of cyclobutadiene compound. The study was done based on the quantum-mechanical computations. All studied compounds were optimized by B3LYP/6-311++G(d,p) basis set of theory. The IR computations showed no imaginary frequency for all molecules. So, the accuracy of computational methods was proved. This study indicates the silicon analogs have more benefits based on the structural and stability properties than the carbon analog.

The aim of this work was to develop and validate the assay test for Tetrabenazine in the pharmaceutical dosage forms by HPLC. The assay method by HPLC was found to be linear in the concentration range of 20 to 100 µg/mL. The mobile phase was composed of acetonitrile and buffer pH: 6.8 potassium dihydrogen phosphate (60:40 v/v) the flow rate of 1 mL/min using UV detection at 215 nm. The results of the analysis were validated by recovery studies. The percentage recovery method was found to be 99.33-100.87%. The LOD and LOQ were found to 0.04 µg/mL and 0.15 µg/mL. All the parameters of validation were in the acceptable range. This developed method was successfully applied to estimate the amount of Tetrabenazine in the tablets.

In this project, keggin-type polyoxometalate, cationic exchange Q5PMoV2O40 (denoted as TBA-PMoV) was synthesized to produce a recovarable catalyst. This catalyst was characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), Field Emission scanning electron microscopy (FESEM) and UV-vis diffuse reflectance spectroscopy (UV-DRS). The synthesized catalyst showed high photocatalytic activity in the degradation of methylene blue as a pollutant under UV light irradiation. The effect of various factors such as catalyst amount, contact time and pH on degradation of methylene blue (denoted as MB) were investigated. Formal batch adsorption studies was applied for investigation of effects of various parameters, such as initial solution pH, initial dye concentration, catalyst amount, temperature, etc. Optimization results for 20 mg/L methylene blue showed that maximum degradation efficiency 96.8 % at the optimum conditions was found to be: catalyst amount 25 mg, pH= 7.6 and time 60 min at ambient pressure and temperature.

Quantum-chemical calculations using the Density Functional Theory (DFT) approach for structural analysis of the new dichroic mono azo dye: Sodium (E)-5-((4-carboxylatophenyl)diazenyl)-2-hydroxybenzoate (S) (trans isomer) was carried out using B3LYP methods with 6-311+G* basis set. After calculations, the new mono azo dye was synthesized. UV, FT-IR and 1H NMR spectra of the compound S are reported. The electronic spectrum of the mono azo dye S was also carried out in the water solution. Interpretation of absorption strips in UV region of spectrum was also reported. On the basis of the polyvinyl alcohol (PVA) and the new dichroic synthesized azo dye polarizer film (?max=388 nm) with effect of polarization (PE = 97%) was developed. The main spectral-polarization parameters (transmittance, optical density) of stretched PVA-films were measured and discussed. It was also established that oriented colored PVA-films is phenomenon of anisotropy of thermal conductivity (??? / ??). Thermal conductivity in the direction of orientation (???) is higher than in the direction perpendicular to the orientations (??). The developed thermostable polarizer film was used in polarizing microscopes, circular polarizers, magnetometers, spectropolarimeters and electrical signals sensors.

A study of quantitative structure-activity relationship (QSAR) is applied to a set of 24 molecules derived from diarylaniline to predict the anti-HIV-1 biological activity of the test compounds and find a correlation between the different physic-chemical parameters (descriptors) of these compounds and its biological activity, using principal components analysis (PCA), multiple linear regression (MLR), multiple non-linear regression (MNLR) and the artificial neural network (ANN). We accordingly proposed a quantitative model (non-linear and linear QSAR models), and we interpreted the activity of the compounds relying on the multivariate statistical analysis. The topological descriptors were computed with ACD/ChemSketch and ChemBioOffice14.0 programs. A correlation was found between the experimental activity and those obtained by MLR and MNLR such as ( Rtrain = 0.886 ; R2train = 0.786 ) and (Rtrain = 0.925 ; R2train = 0.857 ) for the training set compounds, and ( RMLR-test = 0.6 ) and ( RMNLR-test = 0.7 ) for a randomly chosen test set of compounds, this result could be improved with ANN such as ( R = 0.916 and R2 = 0.84 ) with an architecture ANN (6-1-1). To evaluate the performance of the neural network and the validity of our choice of descriptors selected by MLR and trained by MNLR and ANN, we used cross-validation method (CV) including ( R = 0.903 and R2 = 0.815 ) with the procedure leave-one-out (LOO). The results showed that the MLR and MNLR have served to predict activities, but when compared with the results given by an 6-1-1 ANN model. We realized that the predictions fulfilled by the latter model were more effective than the other models. The statistical results indicated that this model is statistically significant and showing a very good stability towards the data variation in leave-one-out (LOO) cross validation.