Abstract

      Oil is the most important natural resources in Iraq and represents the goal to others as well as Iraqi people. It is gift from God to all Iraqi people now and future. So we must maintain it and invest its revenue that achieve development in country and ensure the next generations' rights in it without external costs or negative externalities from extracted and invested it.

    The most problems that we attempt to solve by this research are the exhausted, environmental degradation and theft from next generation that produced with oil contracts between Iraq and foreign companies. From here was th

The δ-mixing of γ-transitions in 70As populated in the 32 70 70 33 Ge p n As (, ) γ reaction is calculated in the present work by using the a2-ratio methods. In one work we applied this method for two cases, the first one is for pure transition and the sacend one is for non pure transition, We take into account the experimental a2-coefficient for previous works and δ -values for one transition only.The results obtained are, in general, in a good agreement within associated errors, with those reported previously , the discrepancies that occur are due to inaccuracies existing in the experimental data of the previous works.

Hepatitis C virus (HCV) is a liver disease that affects14 million people. Feasible research was conducted for identifying the genotypes and allele frequency of some single nucleotide polymorphisms (SNPs) of the IL-28β genes and their predictive role in disease incidence in Iraqi patients. The SNPs (rs28416813, rs4803219, rs11881222, and rs8103142) of IL-28β have been associated with susceptibility to several diseases. Ninety eight (98) HCV patients were included in this research; with average age ± SE (42.28 ± 3.44) years. Also, 80 healthy people (with average age ± SE (29.40 ± 2.84) years) were included as a control group. The SNPs were detected by allele-specific PCR (polymerase chain reaction) using specific primers. The re

This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed

 Humanity is confronted with a growing array of environmental challenges that demand immediate attention and cannot be disregarded. One of the issues the world faces is air pollution, which presents a significant risk to both the environment and human well-being. The capitalist system has a great impact on the exacerbation of air pollution and environmental deterioration. This impact is reflected in Caryl Churchill’s post-apocalyptic play Not Not Not Not Not Enough Oxygen (1971). The play presents a futuristic scenario in which humanity faces grave consequences due to the polluting practices of capitalism and the unsustainable exploitation of natural resources. It depicts a future in which environmental degradation drives people

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,