Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect becomes more significant although the heavy oil-stocks is spiked with hydrocarbons like (gas oil, toluene and reformate). Blending of Heavy oil-stocks with hydrocarbons spikes (gas oil, toluene and reformate) form non-ideal mixtures, for which excess volume can be positive or negative depending on nature species. Spiking of Heavy oil-stocks with either gas oil or reformate resulted in negative excess volume. This shrinkage is greater for the lowest boiling point spike as in the case of reformate, While, the presence of methyl groups in aromatic rings results in a positive excess volume, as shown in toluene when blended with 40 stock but a negative excess volume was found when blended with 60 stock and 150 stock. The API gravity of heavy oil-stocks has an effect on excess volume when the oil-stocks spiked with hydrocarbons like (gas oil, toluene and reformate). This 40 stocks as a typical light types resulted in minimum negative excess volume of -0.47 at 30 °C, when it was spiked with the gas oil; while the spiked heavy oil-stock with kerosene shows a maximum excess volume of -15.56 at 40 °C.
On Saturday, May 13, 2023, a glorious day was engraved in the history of Al-Kindy College Medical Journal as it is the day of indexing the journal in the Scopus Database Journals. The journal has paced a strenuous journey to make that achievement.
Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem
Background: Suppression of quorum sensing (QS) that regulates many virulence factors, including antimicrobial resistance, in bacteria may subject the pathogenic microbes to the harmful consequences of the antibiotics, increasing their susceptibility to such drugs. Aim: The current study aimed to make an aqueous crude extract from the soil Proteus mirabilis isolate with the use of the gas chromatography-mass spectrometry (GC-MS) technique for its analysis, and then, study the impact of the extract on clinical isolates of Pseudomonas aeruginosa. Methods: Preparation of crude extracts from P. mirabilis (both organic and aqueous), which were then analyzed by GC-MS to detect the bioactive ingredients. Furthermore, the extract’s capability to i
... Show MoreAbstract
This research aims to analyze the reality of the production process in an assembly line Cars (RUNNA) in the public company for the automotive industry / Alexandria through the use of some Lean production tools, and data were collected through permanence in the company to identify the problems of the line in order to find appropriate to adopt some Lean production tools solutions, and results showed the presence of Lead time in some stations, which is reflected on the customer's waiting time to get the car, as well as some of the problems existing in the car produced such as high temperature of the car, as the company does not take into account customer preferences,
... Show MorePolycystic ovary syndrome (PCOS) is a complex endocrine–metabolic disorder characterized by hyperandrogenism, ovulatory dysfunction, insulin resistance, and chronic inflammation resulting in reproductive and metabolic complications. Traditional metformin therapy improves insulin sensitivity, while newer dual incretin agonists, such as tirzepatide, may offer broader metabolic and ovarian protection. The objective of this study is to investigate whether tirzepatide could alter hormonal parameters, metabolism, inflammation, and histopathology of a testosterone propionate–induced PCOS rat model compared with metformin. Thirty prepubertal female Wistar rats were divided into five groups (n = 6). PCOS was induced by testosterone propionate (1
... Show MoreAbstract This research adopted a novel mixed-method approach combining quantitative analysis and geospatial statistics with artificial intelligence (AI) techniques to evaluate U5MR in the Middle Euphrates provinces of Iraq in 2022. We investigated spatial patterns, socioeconomic determinants and health system factors related to child mortality, Using data from the Iraqi Ministry of Health in 2022. We uncovered significant disparities across the regions, where the highest death rate in Al Diwaniyah province was 33.1 per 1000 and dropped to 16.6 per 1000 live births in al-Muthanna province. An exhaustive statistical analysis brought to the fore the main factors that accounted for such a variation, that is to say population density in rural a
... Show MoreThis study tackles a fourth-order inverse problem involving a cantilever beam with nonlocal conditions to simultaneously calculate the beam’s displacement and an unknown time-dependent coefficient. A finite difference approach is suggested to discretize the hyperbolic fourth-order equation. A stability analysis for the proposed scheme is also provided. The indirect problem is the minimization of the misfit function. The goal of the minimization algorithm is to reduce the gap between the measured (noisy) data and the numerical computed solution provided by the model. To achieve stable results, Tikhonov’s regularization technique is employed, and two numerical test examples are shown to illustrate the suggested scheme's reliabilit
... Show More