There have been many negative phenomena in Iraqi society, especially after the political crises over the last years, such as the spread of violence, the deterioration of the economic situation, the spread of unemployment and poverty, and the disintegration of social ties, divorce, and the entry of the scourge of drugs. Among the most dangerous of these emergent phenomena, the phenomenon of suicide among young people of both sex, which has grown and increased in an unprecedented manner, surpassing all known social norms in Iraqi society and the prevailing religious values. Suicide in Iraqi society has transformed from a simple case to a visible presence in all Iraqi provinces. Suicides cases have registered in all cities of Iraq and of bo

  The purpose of the study is to analyze the extent of the impact of liquidity as an independent variable on profitability as an intermediate variable and the value of banks listed in the Iraq Stock Exchange as a dependent variable, as the research problem is summarized by the fact that most banks focus on profitability as a phased goal without focusing on maximizing its value as a strategic goal by enhancing the wealth of owners and shareholders. On the long term, the research community is represented by the banks listed on the Iraq Stock Exchange, while the research sample was deliberately chosen, which included three private banks such as Baghdad Commercial Bank, the Iraqi Commercial Bank and the Iraqi Investment Bank, an

Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

Numerical study of separation control on symmetrical airfoil, four digits (NACA

0012) by using rotating cylinder with double steps on its upper surface based on the computation of Reynolds-average Navier- Stokes equations was carried out to find the optimum configuration of unconventional airfoil for best aerodynamics performance. A model based on collocated Finite Volume Method was developed to solve the governing equations on a body-fitted coordinate system. A revised (k-w) model was proposed as a known turbulence model. This model was adapted to simulate the control effects of rotating cylinder. Numerical solutions were performed for flow around unconventional airfoil with cylinder to main stream velocities ratio in the range

The research aims to determine optimal urban planning and design indicators of the urban clusters form in hot arid zones through studying of three urban areas in Baghdad, analyzing their urban indicators which include floor area ratio (FAR), urban clusters height, building density or land coverage, green areas, paved areas, shading ratio and how they affect urban temperature. The research reached the conclusion that air outdoor temperature on urban areas affected primarily by shadows casted on the ground, the effect of shaded area equals (5) times the effect of paved areas and (3.7) times the effect of green areas, this means that increasing urban clusters height in hot arid zones could minimize air outdoor temperature, building

Nanoceria have shown numerous unique characteristics, such as biocompatibility and are excellent agents for biological applications. The aim of this study is to investigate cerium oxide nanoparticles for 2, 2- diphenyl-1-picryl-hydrazyl-hydrate (DPPH) free radical scavenging activity and their ability to offer protection against ionizing radiation. In vitro antioxidant activity study of nanoceria particles has shown good free radical scavenging activity for DPPH radical assayed within a concentration range of 0.01 to 0.05 g/l, at higher concentrations of nanoparticles showed reverse trend in absorbance and inhibition indicating this finite rang of concentration is suitable for scavenging free radicals, also nanoparticles were found to ha

The present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) membrane for heavy metal removal from wastewater and study the factors affecting the performance of these two membranes: feed concentrations for heavy metal ions, pressure, and flow rate. The experimental results showed, heavy metals concentration in permeate increase with raise in feed concentrations, decline with increase in flow rate. The raise of pressure, heavy metals concentration decreases for RO membrane, but for NF membrane the concentration decrease and then at high pressure increase. The rejection percentage for chromium in NF and RO is 99.7% and 99.9%, for copper is 98.4% and 99.3%, for zinc is 97.9% and 99.5%, for nickel is 97.2% and

Background: Alveolar ridge expansion is proposed when the alveolar crest thickness is ≤5 mm. The screw expansion technique has been utilized for many years to expand narrow alveolar ridges. Recently, the osseodensification technique has been suggested as a reliable technique to expand narrow alveolar ridges with effective width gain and as little surgical operating time as possible. The current study aimed to compare osseodensification and screw expansion in terms of clinical width gain and operating time. Materials and methods: Forty implant osteotomies were performed in deficient horizontal alveolar ridges (3–5 mm). A total of 19 patients aged 21–59 years were randomized into two groups: the screw expansion group, which invo

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin