Background This study establishes a mathematically consistent and computational framework for the simultaneous identification of two time-dependent coefficients in a one-dimensional second-order parabolic partial differential equation. The considered problem is governed by nonlocal initial, boundary, and integral overdetermination conditions. Methods The direct problem is solved using the Crank-Nicolson finite difference method (FDM), which ensures unconditional stability and second-order accuracy in both spatial and temporal discretizations. The corresponding inverse problem is reformulated as a nonlinear regularized least-squares optimization problem and efficiently solved used the MATLAB subroutine

Three stations were chosen on the water treatment plan of al- madaan .The Samples collected from the (Raw water) and the Sedimentation, filtration and storage water and the drinking water of outlet. Coliform densities T.S and F.C and TS and F.S and total bacterial count as bacteriological pollution indicators, as moste probable number (MPN) method was studied in test. Also some of the chemical characteristics of the water like pH , total suspended solid T.S.S, T.D.D.and S04 , T.Hardness , Ca++ , Mg++ . From the results it were indicated . The study showed the drinking water of outlet (distriputed in system) was agree with WHO criteria and Iraqi limits standards .

Simple, rapid and sensitive spectrophotometric method was proposed for the analysis of metoclopramide hydrochloride (MPH) in pure form as well as in pharmaceutical tablets. The method is based on the diazotization reaction of MPH with sodium nitrite in hydrochloric acid medium to form diazonium salt, which is coupled with 1-naphthol in sodium hydroxide medium to form azo dye, showing absorption maxima at 550 nm. Beer’s law is obeyed in the concentration range of 0.4 – 18 µg mL-1 of MPH with detection limit 0.5448 µg mL-1. The molar absorptivity and Sandell’s sensitivity are 3.4969 × 104 L mol-1 cm-1 and 0.0101 µg cm-2, respectively. The method was successfully applied to the determination of MPH in pharmaceutical tablets with

The pretreatment process can be considered one of the important processes in wastewater treatment, especially coagulation process to decrease the strength of many pollutants. This paper focused on using powdered date seeds as natural coagulant in addition to chemical coagulants (alum and ferric chloride) to find the optimum dosage of each coagulant that makes efficient removal of turbidity and chemical oxygen demand (COD) from domestic wastewater as a pretreatment process, then finding the optimum combined dosages of date seeds with alum, date seeds with ferric chloride that make efficient removal for both pollutants. Concerning turbidity, the optimum dosage for date seeds, alum and ferric chloride were 40 mg/l (79%), 70

In this research, the kinetic studies of four isoenzymes of Asprtate aminotransferase, which partially purified from the urine of chronic renal failure patients were carried out .The four isoenzymes were obeyed Michaelis-Menton's equation and the optimum concentration of their substrate (Aspartic acid) was (166.5x10-3) mole/liter,and their Km values were determined. Four isoenzymesI,II,III,IV have shown an optimum pH at 7.4.The four isoenzymes obeyed Arrhenius equation up to 37º C and their Ea and Q10 constants were determined .

Previous studies indicated that supplementation with antioxidants has a protective effects against oxidative stress–induced damage in type 2 diabetes. In this study we evaluated the antioxidant effects of melatonin on the oxidative stress parameters and microalbuminuria in type 2 DM patients. 30 patients with type 2 DM were treated with 3mg/day melatonin for 90 days. Erythrocytes and plasma MDA and glutathione, fasting plasma glucose, %Hb_AIC, microalbuminuria, total plasma protein and lipid profile were measured each 30 days and compared with those obtained from 20 healthy controls.

A decrease in MDA levels associated with the elevation in GSH levels were observed, compared with the pre–treatment levels.

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow