The research endeavors to harness the benefits stemming from the integration of constraint theory into construction project management, with the primary goal of mitigating project completion delays. Additionally, it employs fuzzy analysis to determine the relative significance of fundamental constraints within projects by assigning them appropriate weights. The research problem primarily revolves around two key issues. Firstly, the persistent utilization of outdated methodologies and a heavy reliance on workforce experience without embracing modern computerized technologies. Secondly, the recurring problem of project delivery delays. Construction projects typically encompass five fundamental constraint types: cost restrictions, tim

The current study aimed to ascertain the levels of matrix metalloproteinase-12 (MMP-12) and Lysyl oxidase (LOX) in osteoporosis patients and their correlation with alkaline phosphatase (ALP), magnesium (Mg), vitamin D (Vit D), calcium (Ca), phosphorus (P), and T-score %. 110 participants recruited from Baghdad Teaching Hospital, Iraq, were enrolled in this study from November 2019 to March 2020). The participants were divided into two groups: Group 1 comprised 60 osteoporotic women and group 2 consisted of 50 healthy women. (MMP and LOX) were estimated using a quantitative enzyme-linked immunosorbent assay (ELISA. The results showed significant differences in serum LOX, age, ALP, Mg, and T-score %, while no significant differences i

Evaluating treatment effect on interferon-alpha in female patients with systemic lupus erythematosus: a case-control study

Recently on the dermatological fields, the serum levels and the roles of Zn, Cu and Mg have been studied especially in acne vulgaris, but the results were controversial. The aim of the present study is to investigate  a relationship between the severity of acne and the serum levels of zinc (Zn), copper (Cu) and magnesium (Mg) and to demonstrate the status of serum levels of zinc, copper, and magnesium in Iraqi male patients with acne vulgaris and to compare it with those of healthy controls.This case controlled study was conducted in the Department of Dermatology and Venerology and in the Poisoning Consultation Center of Baghdad Teaching Hospital between May 2009 to January 2010. Forty- five male patients with acne vulgaris, their a

This study examines the vibrations produced by hydropower operations to improve embankment dam safety. This study consists of two parts: In the first part, ANSYS-CFX was used to generate a three-dimensional (3-D) finite volume (FV) model to simulate a vertical Francis turbine unit in the Mosul hydropower plant. The pressure pattern result of the turbine model was transformed into the dam body to show how the turbine unit's operation affects the dam's stability. The upstream reservoir conditions, various flow rates, and fully open inlet gates were considered. In the second part of this study, a 3-D FE Mosul dam model was simulated using an ANSYS program. The operational turbine model's water pressure pattern is conveyed t

The ability of beans (Phaseolus vulgaris L.) to uptake three pharmaceuticals (diclofenac, mefenamic acid and metronidazole) from two types of soil (clay and sandy soil) was investigated in this study to explore the human exposure to these pharmaceuticals via the consumption of beans. A pot experiment was conducted with beans plants which were grown in two types of soil for six weeks under controlled conditions. During the experiment period, the soil pore water was collected weekly and the concentrations of the test compounds in soil pore water as well as in plant organs (roots, stems and leaves) were weekly determined.
The results showed that the studied pharmaceuticals were detected in all plant tissues; their concentration

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an