A new simple sensitive and selective spectrophotometric method has been
developed for the analysis of vanadium(V) in three randomly chosen samples from
river water at different locations by continuous flow injection analysis. The method
based on the oxidation of pyrogallol by vanadium(V) in acidic solution to form color
species and the same species was determined using homemade Ayah 6SX1-T-2D
solar cell analyser . Chemical and physical parameters were investigated using the
high intensity of snow white light emitted diode as a source. The linear dynamic
range for the instrument response versus vanadium(V) concentration was 1-200
mg.L-1 with correlation coefficient r = 0.9920. The limit of detection (S/N=3) was 70<

A new simple sensitive and selective spectrophotometric method has been developed for the analysis of vanadium(V) in three randomly chosen samples from river water at different locations by continuous flow injection analysis. The method based on the oxidation of pyrogallol by vanadium(V) in acidic solution to form color species and the same species was determined using homemade Ayah 6SX1-T-2D solar cell analyser . Chemical and physical parameters were investigated using the high intensity of snow white light emitted diode as a source. The linear dynamic range for the instrument response versus vanadium(V) concentration was 1-200 mg.L-1 with correlation coefficient r = 0.9920. The limit of detection (S/N=3) was 70 ng/ sample from the step

A simple indirect spectrophotometric method for determination of mebendazol in pure and pharmaceutical formulation was presented in this study. UV-Visible spectrophotometry using the optimal conditions was developed for determination of mebendazole in pure drug and different preparation samples. The method is based on the oxidation of drug by nbromosuccinimide with hydrochloric acid and the left amount of oxidizing agent was determined by the reaction with tartarazine and the absorbance was measured at 428 nm. Calibration curves were linear in the range of 5 to 30 µg.mL-1 with molar absorptivity 8437.2 L.mol-1 .cm-1 . The limits of detection and quantification were determined and found to be 0.7770 µg.mL-1 and 2.3400 µg.mL-1 respec

The Co (II), Ni (II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II) complexes of mixed of amino acid (L-Alanine ) and Trimethoprim antibiotic were synthesized. The complexes were characterized using melting point, conductivity measurement and determination the percentage of the metal in the complexes by flame (AAS). Magnetic susceptibility, Spectroscopic Method [FT-IR and UV-Vis]. The general formula have been given for the prepared mixed ligand complexes [M(Ala)2(TMP)(H2O)] where L- alanine (abbreviated as (Ala ) = (C5H9NO2) deprotonated primary ligand, L- Alanine ion .= (C5H8NO2-) Trimethoprim (abbreviated as (TMP ) = C10H11N3O3S M(II) = Co (II),Ni(II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II). The results showed that the deprotonated L- Alanine b

Complexes reaction of Fe+2, Cd+2, Hg+2 and Ag+ with the 2-thiotolylurea were prepared in ethanolic medium with the (1:1) M:L ratio yielded a series of neutral complexes. The prepared complexes were characterized using flame atomic absorption, micoelemental analysis (C.H.N), chloride content (Mohr Method) , FT.IR and UV-Vis spectroscopic, as well as magnetic susceptibility and conductivity measurement. From the above data, the proposed molecular structure for Fe+2, Cd+2 and Hg+2 complexes are tetrahedral geometry while Ag+ complex is trigonal structure.

           A new ligand type (O₂) [2,3-O-diacetyl-5,6-O-benzylidene L- ascorbic acid] [L] and its complexes of general formula [M(L)₂(X)(Y)]Cl_n (where: M=Cr^III ,X=Y=H₂O, n=3; Co^II, X = Y = 0, n= 2; Ni^II and Cu^II, X = Cl, Y = H₂O, n= 1; Zn^II, X = Y = H₂O,n = 2) are reported. The ligand was prepared in two steps; first step involved the synthesis of [5,6-O-benzylidene-L-ascorbic acid] (A). In second step derivative-A was then reacted with acetyl chloride and anhydrous pyridine as a base to give the titled ligand. Metal complexes of the ligand with Cr^III,Co^II

A newly photometric analytical method characterized by its speed and sensitivity was developed for the determination of folic acid in pure and pharmaceutical samples via its oxidation to reddish-orange coloured complex through oxidation by cerium (IV) sulphate in aqua medium using homemade Ayah 3Sx3-3D-solar cell CFI photometer. The colored species were determined using supper bright green light emitting diode (LED) as a source. A 100μl was taken as a best sample volume for the determination of folic acid. The linearity of calibration curve for the instrument response versus folic acid concentration was 0.005-20 mmol.L-1 while the L.O.D. was 0.5  mol.L-1 from the stepwise dilution for the minimum concentration of lowest concentration

Simple, sensitive and accurate two methods were described for the determination of terazosin. The spectrophotometric method (A) is based on measuring the spectral absorption of the ion-pair complex formed between terazosin with eosin Y in the acetate buffer medium pH 3 at 545 nm. Method (B) is based on the quantitative quenching effect of terazosin on the native fluorescence of Eosin Y at the pH 3. The quenching of the fluorescence of Eosin Y was measured at 556 nm after excitation at 345 nm. The two methods obeyed Beer’s law over the concentration ranges of 0.1-8 and 0.05-7 µg/mL for method A and B respectively. Both methods succeeded in the determination of terazosin in its tablets

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St