This study aimed to evaluate the sustainable efficiency and calculate the sustainable value, opportunity cost and revenue to cost of potato production farms in Baghdad Governorate. Data were collected from a random sample of 102 spring potato producers in Baghdad governorate for the year 2022, the value-added function was estimated using three levels: economic (seeds and space), and social (education level), while environmental represented by (residual and volatile of nitrogen). Effective resources were calculated to extract the sustainability value- SV appeared on an average of 18023.15 thousand Iraqi dinars. Positive relationship with residual nitrogen and productivity, and Inverse relationship to the amount of volatile nitrogen.

The Geological modeling has been constructed by using Petrel E&P software to incorporate data, for improved Three-dimensional models of porosity model, water saturation, permeability estimated from core data, well log interpretation, and fault analysis modeling.

Three-dimensional geological models attributed with physical properties constructed from primary geological data. The reservoir contains a huge hydrocarbon accumulation, a unique geological model characterization with faults, high heterogeneity, and a very complex field in nature.

The results of this study show that the Three-dimensional geological model of Khasib reservoir, to build the reservoir model starting with evaluation of reservoir to interpretation o

Seventy of Klebsiella pneumoniae isolates had been collected from some Hospitals in Baghdad city from October to December 2017. The 70 isolates were taken from diverse clinical specimens. All K. pneumoniae isolates were identified based on API 20 E and Vitek2 compact system. Antibiotics sensitivity test was carried out toward 10 antibiotics using discs diffusion method. The level of antibiotics resistance was 81.42% for Ceftriaxone, whereas the low level of antibiotics resistance was 37.14% for Piperacillin. K. pneumoniae isolates were typed genotypically by using two different methods of amplification, multiplex-PCR and enterobacterial repetitive intergenic consensus (ERIC)-PCR typing methods. Results showed that out of 70 isolates, there

   Asphaltenes are a solubility class described as a component of crude oil with undesired characteristics. In this study, Sharqy Baghdad heavy oil upgrading was achieved utilizing the solvent deasphalting approach as asphaltenes are insoluble in paraffinic solvents; they may be removed from heavy crude oil by adding N-Hexane as a solvent to create deasphalted oil (DAO)of higher quality. This method is known as Solvent De-asphalting (SDA). Different effects have been assessed for the SDA process, such as solvent to oil ratio (4-16/1 ml/g), the extraction temperature (23 ºC) room temperature and (68 ºC) reflux temperature at (0.5 h mixing time with 400 rpm mixing speed). The best solvent deasphalting results were obtained at room temp

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and