A simple, low cost and rapid flow injection turbidimetric method was developed and validated for mebeverine hydrochloride (MBH) determination in pharmaceutical preparations. The developed method is based on forming of a white, turbid ion-pair product as a result of a reaction between the MBH and sodium persulfate in a closed flow injection system where the sodium persulfate is used as precipitation reagent. The turbidity of the formed complex was measured at the detection angle of 180° (attenuated detection) using NAG dual&Solo (0-180°) detector which contained dual detections zones (i.e., measuring cells 1 & 2). The increase in the turbidity of the complex was directly proportional to the increase of the MBH concentration

Flame atomic absorption spectrophotometer (FAAS) was used in this study to determine the concentrations of heavy metals such as Ca, Fe, Mn, Cd, Co, Cr, Ni, Cu, Pb and Zn in some food additives of Iraq. The order of metal contents in food additives was found to be Ca ˃ Mn ˃ Fe ˃ Cu ˃ Zn ˃ Pb ˃ Cr ˃ Ni ˃ Co ˃ Cd. The concentration level of each metal was compared with that recommended by food agriculture organisation (FAO) and world health organisation (WHO). Calibration curves were linear for all standard solutions of heavy metals in the range starting from 0.02-0.4 mg/kg for Cd to 11-100 mg/kg for Ca. The correlation coefficients values (R2) of calibrations were investigated and ranged from 0.9971 for Cr to 0.9999 for Ca. Th

            Spectrophotometric method was developed for the determination of copper(II) ion. Synthesized (2,2[O-Tolidine-4,4-bis azo]bis[4,5-diphenyl imidazole]) (MBBAI) was used as chromogenic reagent at pH=5. Various factors affecting complex formation, such as, pH effect, reagent concentration, time effect and temperature effect, have been considered and studied. Under optimum conditions concentration ranged from (5.00-80.00) µg/mL of copper(II) obeyed Beer`s Low. Maximum absorption of the complex was 409nm with molar absorpitivity 0.127x10⁴ L mol^-1 cm^-1. Limit of detection(LOD) and Limit of quantification were 1.924 and 6.42 μg/mL, respectively.

A simple, low cost and rapid flow injection turbidimetric method was developed and validated for mebeverine hydrochloride (MBH) determination in pharmaceutical preparations. The developed method is based on forming of a white, turbid ion-pair product as a result of a reaction between the MBH and sodium persulfate in a closed flow injection system where the sodium persulfate is used as precipitation reagent. The turbidity of the formed complex was measured at the detection angle of 180° (attenuated detection) using NAG dual&Solo (0-180°) detector which contained dual detections zones (i.e., measuring cells 1 & 2). The increase in the turbidity of the complex was directly proportional to the increase of the MBH concentration

A fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti