The process of capital investment appraisal takes hold the attention of managers and accountants of the industrial companies. This process involves the use of multiple and diverse financial evaluation methods to measure the economic attractiveness of capital investment peojects. This multiplicity and diversity of financial evaluation metods have been the motive of this research to: investigate some organizational variables such as the desired objectives, identify managerial procedures which regulate the capital investment process, specify evaluation methods and examine the relationships between these variables and evaluation methods actually used by a sample of public industrial companies in Jordan.

    The data wa

Low-dimensional materials have attracted significant attention in developing and enhancing the performance of quantum well lasers due to their extraordinary unique properties. The optical confinement factor is one of the most effective parameters for evaluating the optimal performance of a semiconductor laser diode when used to measure the optical gain and current threshold. The optical confinement factor and the radiative recombination of single quantum wells (SQW) and multi-quantum wells (MQW) for InGaAsP/InP have been theoretically studied using both radiative and Auger coefficients. Quantum well width, barrier width, and number of quantum wells were all looked at to see how these things changed the optical confinement factor and

This study aimed to evaluate serum levels of steroid hormones and human chorionic gonadotropin (hCG) hormone in preeclamptic Iraqi pregnancies compared to those of healthy pregnancies.This study enrolled 120 pregnant women, divided into four groups:1. 30 healthy pregnant women.2. 37 pregnant women with mild preeclampsia3. 53 pregnant women with severe preeclampsia4. 90 pregnant women with preeclampsia Preeclamptic women and their severe cases but not mild cases had significantly (P<0.01) increased levels of serum hCG as compared with healthy pregnancies. By contrast, sera levels of estradiol were significantly (P<0.01) decreased in total preeclamptic groups and their severe cases but not in mild group as compared to healthy pregnant wome

Ameloblastic fibroma is a rare benign tumor usually affects the first two decades of life. The neoplasm is more predominant in mandibular molar-premolar region and rarely affects the maxilla. In this report, we present a couple of Ameloblastic fibroma cases, affecting boys at their 1st decade. The lesions were presented as swellings of their maxilla, which is atypical location. Radiographic images showed well-defined radiolucency containing areas of radio-opacities and impacted teeth. Differential diagnosis was established as cystic/neoplastic conditions. The lesions were incised and histopathologically diagnosed as Ameloblastic fibroma, since they were composed of immature odontogenic mesenchymal and epithelial cells showing different c

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are