In Iraq, more than 1031 school projects have been halted due to disputes and claims resulting from financial, contractual, or other issues. This research aims to identify, prioritize, and allocate the most critical risk factors that threaten these projects’ success for the duration (2017-2022). Based on a multi-step methodology developed through systematic literature reviews, realistic case studies, and semi-structured interviews, 47 risk factors were identified. Based on 153 verified responses, the survey reveals that the top-ranked risk factors are corruption and bribery, delaying the payments of the financial dues to the contractors or sub-contractors, absence of risk management strategy, multiple change orders due

Hard-grade asphalt binders like AC20-30 typically exhibit excessive stiffness, reduced penetration, and compromised workability, necessitating modification before use in paving applications. This study evaluates the efficacy of regular polyalphaolefin (PAO), a synthetic olefin-based lubricant, as a performance-enhancing modifying agent for such binders. AC20-30 was blended with PAO at dosages ranging from 2 wt.% to 10 wt.%, and the modified binders were characterized via penetration, ductility, softening point, and rotational viscosity measurements, alongside advanced rheological and chemical-morphological analyses. Incorporating PAO in AC20-30 asphalt progressively reduced the binder stiffness and enhanced its flexibility, with all modifie

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

Rutting is mainly referring to pavement permanent deformation, it is a major problem for flexible pavement and it is a complicated process and highly observed along with many segments of asphalt pavement in Iraq. The occurrence of this defect is related to several variables such as elevated temperatures and high wheel loads. Studying effective methods to reduce rutting distress is of great significance for providing a safe and along-life road. The asphalt mixture used to be modified by adding different types of additives. The addition of additives typically excesses stiffness, improves temperature susceptibility, and reduces moisture sensitivity. For this work, steel fibres have been used for modifying asphalt mixture as they incorp

The escalating generation of industrial waste alongside the growing demand for high-performance, environmentally sustainable drilling fluids presents critical challenges to the oil and gas sector. Conventional drilling fluid additives are predominantly synthesized from virgin materials, contributing to resource depletion and environmental burden. Objectives: This study pioneers a circular economy approach by synthesizing silica nanoparticles (SiO2NPS) and alumina nanoparticles (Al2O3NPs) entirely from locally sourced industrial waste — bentonite clay and aluminum scrap, respectively — and evaluating their performance as functional additives in water-based drilling fluids (WBDFs). Novelty: To the best of our knowledge, this represents th