A modification to cascaded single-stage distributed amplifier (CSSDA) design by using active inductor is proposed. This modification is shown to render the amplifier suitable for high gain operation in small on-chip area. Microwave office program simulation of the Novel design approach shows that it has performance compatible with the conventional distributed amplifiers but with smaller area. The CSSDA is suitable for optical and satellite communication systems.

The simple and available technique of colorimetry and indirect X-ray fluorescence determination of tetracycline hydrochloride (in the form of colored complex with iron(III) ions) and cyanocobalamine (in the form of the colored thiocyanate complex with cobalt(II) ions) is offered. The analytes were separated from the accompanying components by sorption to polyurethane foam based on ethers. The conditions of sorption separation and measurement of analytical signal of these substances are optimized. The obtained results of tetracycline drugs and injection solution B₁₂ vitamin are in satisfactory agreement with data declared by the manufacturer.

Background : Gastroesophageal reflux disease (GERD) is one of chronic gastrointestinal diseases in which patient may be asymptomatic or was complained from heartburn and regurgitation or pulmonary symptoms. Aim of the study : Examine the serum level of sHLA-G in GERD patients and can be used as a biomarker for early detection of GERD disease. Materials and methods : The design of the study was a case- control prospective enrolled forty patients consulted Gastroenterology Unit- Al-Kindy Teaching Hospital, were diagnosed as GERD by their physician, and compared to second forty control healthy group form January-2023 to May-2024. Serum used for quantitative assessment of soluble HLA-G (sHLA-G) using a sandwich enzyme-linked immunosorbent a

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope