The paper deals with claims in construction projects in Iraq and studies their types, causes, impacts, resolution methods and then proposes a management system to control the impacts of claims. Two parts have been done to achieve the research objective (theoretical part and practical part). The findings showed that the main types of the claims are extra work claims, different site condition claims, delay claims and the main causes of the claims are variation of the orders, design errors and omission, delay in payments by owner, variation in quantities and scheduling errors. The claims have bad impacts on the cost by increasing (10% to 25%) and also on the duration of the project by increasing from (25% to 50%).The negotiation is the main

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The Iraqi government seeks to overcome the financial crisis by investing and privatizing some projects to achieve sustainable growth. Most of the investment projects in Iraq suffer from many constraints that greatly impact the success of these projects. A survey of the opinions of a group of experts was conducted to identify the most important constraints facing the investment process in Iraq. Then the experts' answers were arranged in a closed questionnaire and distributed to the research sample for which the statistical analysis was conducted. Through it, the most important (17) factors that had the greatest impact on the failure of investment projects in Iraq were reached. One of the main constraints was

Background: The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor historically recognized for its role in the regulation of toxicity mediated by environmental chemicals. Recent research points to AhR's critical participation in male reproductive physiology, particularly in spermatogenesis, hormone signaling, and the maintenance of sperm quality. Both endogenous ligands (e.g., dietary and gut microbiota-derived metabolites) and exogenous pollutants (e.g., dioxins and benzo-α-pyrene) influence AhR-mediated pathways, making it a key link between environmental exposures and male fertility. Results: This review highlights AhR's influence on the male reproductive system, emphasizing the role of endogenous AhR ligands an

The aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas

This study aimed at some of the criteria used to determine the form of the river basins, and exposed the need to modify some of its limitations. In which, the generalization of the elongation and roundness ratio coefficient criterion was modified, which was set in a range between (0-1). This range goes beyond determining the form of the basin, which gives it an elongated or rounded feature, and the ratio has been modified by making it more detailed and accurate in giving the basin a specific form, not only a general characteristic. So, we reached a standard for each of the basins' forms regarding the results of the elongation and circularity ratios. Thus, circular is (1-0.8), and square is (between 0.8-0.6), the blade or oval form is (0.6-0

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo