The high viscosity of heavy oil is a crucial factor that strongly affects its up-stream recovering, down-stream surface transporting and refining processes. Economical methods for recovering the heavy oil and reducing is very important and related to capital and/or operating cost. This research studies the treatment of Iraqi heavy crude oil, which characterize with high viscosity and low API which makes transportation of heavy crude oil a difficult mission, needs for treatment to reduce viscosity for facilitating transportation and processing. Iraqi heavy crude oil was used Sharqi Baghdad, which obtained from Baghdad east oil fields with API 22.2º.Many kinds of additives were used to reduce the viscosity, experiments were performed o

Empirical equation has been presented to predict the optimum hydrodynamic
pressure gradient with optimum mud flow rate (one equation) of five Iraqi oil wells
to obtain the optimum carrying capacity of the drilling fluid ( optimum transport
cuttings from the hole to the surface through the annulus).
This equation is a function of mud flow rate, mud density and penetration
rate without using any charts or graphs.
The correlation coefficient accuracy is more than 0.9999.

Efficient cuttings transport and hole cleaning are very important factors for obtaining an effective drilling operation. In an inclined and horizontal drilling, hole cleaning issue is a common and complex problem.

   The scope of this research is to study the drilling parameters which affect hole cleaning in Iraqi directional wells through studying and analyzing some drilled wells ( vertical , directional (30 degree) , directional (60 degree) and horizontal ).An excel sheet is prepared to calculate carrying capacity index which represents an indicator for good hole cleaning in different sections. The study indicated through the field investigations, practical experiences and theoretical calculations tha

In this study, a proposed process for the utilization of hydrogen sulphide separated with other gases from omani natural gas for the production of sulphuric acid by wet sulphuric acid process (WSA) was studied. The processwas simulated at an acid gas feed flow of   5000 m³/hr using Aspen ONE- V7.1-HYSYS software. A sensitivity analysis was conducted to determine the optimum conditions for the operation of plant. This included primarily the threepacked bed reactors connected in series for the production of sulphur trioxidewhich represented the bottleneck of the process. The optimum feed temperature  and catalyst bed volume for each reactor were estimated and then used in the simulation of the whole process for tw

Reuse of spent hydrodesulphurization (HDS) of middle petroleum fractions catalyst CoMo/γAl₂O₃ was accomplished via removal of coke and contaminants such as vanadium, Iron, Nickel, and sulfur. Three processes were adopted; extraction, leaching, decoking. Soluble and insoluble coke was removed. Leaching step used three different solvents (oxalic acid, ammonium peroxydisulfate and oxalic acid + H₂O₂) in separate in order to remove contaminant metals (V, S, Ni and Fe).

   The effect of soluble coke removal on leaching step was studied. It was found that the removal of soluble coke significantly enhances the leaching of contaminants and barely affected the removal of active metals

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

In the present study the performance of drying process of dffirent solid materials by batch fluidized bed drying
under vacuum conditions was investigated. Three, different solid materials, namely; ion exchange resin-8528,
aspirin and paracetamol were used. The behavior of the drying curves as well as the rate of drying of these
materials had been studied. The experiments were caried out in a 0.0381 m column diameter fluidized by hot
air under yacuum conditions. Four variables affecting on the rate of drying were studied' these variables are
vacuum pressure (100 - 500 mm Hg), air temperature (303-323 K), particle size (0.3-0.8 mm) and initial
moisture content (0.35-0.55 g/g solid)-for resin and (0.1-0.2 g/g soltid) for a

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi